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

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

00:00:59.060 longer and how to live better. I have a complete fascination and obsession with this topic. I

00:01:04.760 practice it professionally and I've seen firsthand how access to information is basically all people

00:01:09.920 need to make better decisions and improve the quality of their lives. Curating and sharing this

00:01:15.100 knowledge is not easy. And even before starting the podcast, that became clear to me. The sheer volume

00:01:20.380 of material published in this space is overwhelming. I'm fortunate to have a great team that helps me

00:01:25.800 continue learning and sharing this information with you. To take one example, our show notes are in a

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

00:01:54.200 reasons. Now, the first and most important of these is trust. I'm not sure how you can trust me if I'm

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

00:02:05.080 it. Another reason selling ads doesn't feel right to me is because I just know myself. I have a really

00:02:11.280 hard time advocating for something that I'm not absolutely nuts for. So if I don't feel that way about

00:02:16.660 something, I don't know how I can talk about it enthusiastically. So instead of selling ads, I've chosen

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

00:02:41.660 the benefits above and beyond what's available for free. It's that simple. It's my goal to ensure

00:02:47.300 that no matter what level you choose to support us at, you will get back more than you give.

00:02:52.880 So for example, members will receive full access to the exclusive show notes, including other things

00:03:00.380 that we plan to build upon, such as the downloadable transcripts for each episode. These are useful beyond

00:03:07.100 just the podcast, especially given the technical nature of many of our shows. Members also get

00:03:12.900 exclusive access to listen to and participate in the regular ask me anything episodes. That means

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. 0.99

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 0.82

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 1.00

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 0.98

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, 0.53

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 0.93

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 0.51

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 0.88

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 0.51

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 0.85

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 0.66

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 1.00

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. 0.99

00:44:11.640 I think any woman listening to this who's been pregnant, that's got to be one of their 1.00

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 0.96

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 1.00

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? 1.00

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 0.99

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, 1.00

00:52:25.620 it actually doesn't get replaced with fat. And that is what we call the dense breast tissue. 1.00

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, 0.75

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 0.99

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 0.99

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 1.00

00:53:36.620 they're premenopausal in their childbearing age, they still have a lot of glandular tissue. That means a 1.00

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 1.00

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 1.00

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 1.00

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, 1.00

00:55:35.680 so there's a hundred women and we absolutely know that they have breast cancer and we subject them to 0.94

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 0.73

00:57:20.340 take a hundred women who have very, very dense breast tissue and drive your specificity down to 50%. 0.97

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 0.84

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 0.88

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. 1.00

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 1.00

01:03:26.900 be more likely to have dense breast tissue, do we have a sense of what percentage of them 1.00

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, 0.94

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 0.94

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 0.91

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 0.99

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? 0.89

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 0.63

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 0.62

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 0.86

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. 0.99

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.

02:11:48.100 You can find all of this information and more at peteratiamd.com forward slash podcast.

02:11:53.380 There you'll find the show notes, readings, and links related to this episode. You can also find my blog

02:11:59.060 at peteratiamd.com. Maybe the simplest thing to do is to sign up for my subjectively non-lame once a

02:12:04.940 week email where I'll update you on what I've been up to, the most interesting papers I've read,

02:12:09.220 and all things related to longevity, science, performance, sleep, etc. On social, you can find

02:12:14.920 me on Twitter, Instagram, and Facebook, all with the ID peteratiamd. But usually Twitter is the best

02:12:20.560 way to reach me to share your questions and comments. Now for the obligatory disclaimer, this

02:12:24.700 podcast is for general informational purposes only and does not constitute the practice of medicine,

02:12:29.300 nursing, or other professional healthcare services, including the giving of medical advice.

02:12:34.880 And note, no doctor-patient relationship is formed. The use of this information and the

02:12:39.840 materials linked to the podcast is at the user's own risk. The content of this podcast is not intended

02:12:44.820 to be a substitute for professional medical advice, diagnoses, or treatment. Users should not

02:12:49.920 disregard or delay in obtaining medical advice for any medical condition they have and should seek

02:12:54.620 the assistance of their healthcare professionals for any such conditions. Lastly, and perhaps most

02:13:00.140 importantly, I take conflicts of interest very seriously. For all of my disclosures, the companies

02:13:04.940 I invest in and or advise, please visit peteratiamd.com forward slash about.

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

Summary

Transcript