Rajpaul Attariwala transitioned from engineering to radiology because he wanted to apply his engineering background to create a unique MRI scanner capable of constructing whole-body images with unmatched resolution. He found that radiology, with its focus on technology and imaging, was the perfect field to combine his engineering skills with his interest in the human body and physiology.
An x-ray works by using high-energy wavelengths that penetrate the body. Dense structures like bones absorb the x-ray beam, appearing white on the film, while less dense structures like soft tissues and air allow the beam to pass through, appearing black. The main limitation is that x-rays provide a 2D image of 3D structures, leading to overlapping layers of tissue that can obscure details.
A T1 weighted MRI image highlights fat, making it appear bright and providing excellent anatomical detail. A T2 weighted image highlights water, making it appear bright, and is useful for detecting edema and other abnormalities where water content is increased. T2 images take longer to acquire due to the longer echo time required to capture both fat and water signals.
MRI is considered safer than CT scans because it does not use ionizing radiation, which can damage cells and DNA, potentially leading to cancer. MRI uses magnetic fields and radio waves to produce images, making it a radiation-free imaging tool.
The risks associated with cancer screening include false positives, where a test indicates cancer when it is not present. This can lead to unnecessary follow-up tests, biopsies, and emotional distress. False positives can result in overdiagnosis and overtreatment, which may carry their own risks and complications.
Diffusion-weighted imaging (DWI) in MRI works by measuring the movement of water molecules in tissues. It detects areas where water diffusion is restricted, which often indicates high cellular density, such as in tumors. DWI is particularly useful for detecting cancer because it can highlight areas of abnormal tissue that may be cancerous.
The Tesla rating in MRI machines indicates the strength of the magnetic field. Higher Tesla ratings (e.g., 3T) allow for better resolution and faster imaging but can also increase the risk of artifacts and heating. Lower Tesla ratings (e.g., 1.5T) provide good penetration and are often optimized for whole-body imaging without the drawbacks of higher fields.
Standardization in MRI technology is important because it ensures consistency and reliability in imaging results across different machines and facilities. Without standardization, the quality and interpretation of MRI scans can vary widely, leading to potential misdiagnoses and inconsistent patient care.
Potential advancements in MRI technology in the next 5-10 years include faster scanning times, improved resolution, and the integration of machine learning to enhance image analysis and diagnostic accuracy. Advances in computational power and software could also enable more sophisticated image processing and real-time analysis.
Machine learning impacts the field of radiology by assisting radiologists in analyzing images more efficiently and accurately. It can help in identifying patterns, detecting abnormalities, and even serving as a second reader to reduce the likelihood of missing critical findings. Machine learning can also aid in the analysis of longitudinal studies by comparing changes over time.
Hey everyone, welcome to the Peter Attia Drive. I'm your host, Peter Attia.
The drive is a result of my hunger for optimizing performance, health, longevity, critical thinking, along with a few other obsessions along the way. I've spent the last several years working with some of the most successful top performing individuals in the world. And this podcast is my attempt to synthesize what I've learned along the way to help you live a higher quality, more fulfilling life. If you enjoy this podcast, you can find more information on today's episode and other topics at peteratiamd.com.
Hey everybody, welcome to this week's episode of The Drive. I'd like to take a couple of minutes to talk about why we don't run ads on this podcast and why instead we've chosen to rely entirely on listener support. If you're listening to this, you probably already know, but the two things I care most about professionally are how to live longer and how to live better.
I have a complete fascination and obsession with this topic. I practice it professionally, and I've seen firsthand how access to information is basically all people need to make better decisions and improve the quality of their lives. Curating and sharing this knowledge is not easy, and even before starting the podcast, that became clear to me. The sheer volume of material published in this space is overwhelming. I'm fortunate to have a great team that helps me continue learning and sharing this information with you.
To take one example, our show notes are in a league of their own. In fact, we now have a full-time person that is dedicated to producing those, and the feedback has mirrored this. So all of this raises a natural question. How will we continue to fund the work necessary to support this? As you probably know, the tried and true way to do this is to sell ads. But after a lot of contemplation, that model just doesn't feel right to me for a few reasons. Now, the first and most important of these is trust.
I'm not sure how you could trust me if I'm telling you about something when you know I'm being paid by the company that makes it to tell you about it. Another reason selling ads doesn't feel right to me is because I just know myself. I have a really hard time advocating for something that I'm not absolutely nuts for. So if I don't feel that way about something,
I don't know how I can talk about it enthusiastically. So instead of selling ads, I've chosen to do what a handful of others have proved can work over time. And that is to create a subscriber support model for my audience. This keeps my relationship with you both simple and honest. If you value what I'm doing, you can become a member and support us at whatever level works for you. In exchange, you'll get the benefits above and beyond what's available for free. It's that simple.
It's my goal to ensure that no matter what level you choose to support us at, you will get back more than you give.
So, for example, members will receive full access to the exclusive show notes, including other things that we plan to build upon, such as the downloadable transcripts for each episode. These are useful beyond just the podcast, especially given the technical nature of many of our shows. Members also get exclusive access to listen to and participate in the regular Ask Me Anything episodes.
That means asking questions directly into the AMA portal and also getting to hear these podcasts when they come out. Lastly, and this is something I'm really excited about, I want my supporters to get the best deals possible on the products that I love. And as I said, we're not taking ad dollars from anyone, but instead what I'd like to do is work with companies who make the products that I already love and would already talk about for free and have them pass savings on to you. Again, the podcast will remain free to all.
but my hope is that many of you will find enough value in one, the podcast itself and two, the additional content exclusive for members to support us at a level that makes sense for you. I want to thank you for taking a moment to listen to this. If you learn from and find value in the content I produce, please consider supporting us directly by signing up for a monthly subscription. My guest this week is Dr. Raj Atariwala. Raj is an amazing guy. I've known him for several years and
He's incredibly well-trained. He first actually went down the engineering pathway doing his PhD in biomedical engineering at Northwestern, then decided he wanted to go into medicine and sort of apply his engineering approach to that. So he went back to medical school, did his residency in radiology, and then went on to specialize in nuclear medicine and spent a great deal of time at some of the top institutions in North America, Memorial Sloan Kettering, UCLA, USC, etc.,
He's now back in Vancouver and what he's been up to for about the past decade has been effectively creating a new way of doing MRI. So he's sort of what I think can only be described as an MRI ninja. And that is to say, he's been able to tinker with the hardware and the software to create a completely revolutionary product and process by which to look at the body using this technology of magnetic resonance. Now,
I think this is a bit of a technical episode, but I also think it's one that anybody who's ever had an x-ray, a CT scan, an ultrasound, an MRI in their life needs to listen to. Why? Because truthfully, most doctors don't actually understand this stuff in great detail. You have to really go out of your way
in medical school and residency to understand radiology. I was obsessed with it. I went out of my way to learn about it. I learned a little bit about it, but obviously nothing to the level of what someone like Raj knows. And so what we did in this episode, which you can sort of divide into two halves is as follows. The first half is sort of a history of radiology. So we start with talking about what an x-ray is, how it works, what the radiation does and doesn't mean, CT scans, ultrasounds, PET scans, nuclear medicine scans, all of these things.
And I promise we've done this in a way that is really geared towards the patient. I think we do a pretty good job of always bringing it back to language that makes sense and we don't get terribly lost in the physics. And of all areas in medicine where you can get lost in the physics, this is head and shoulders above the rest. Second half of this episode, we really do this deep dive into cancer screening and the
This particular type of MRI technology that Raj has almost single-handedly developed, although he would probably bristle at the sound of me saying that because he's just such a modest fellow.
What I enjoy about this episode is it gives me a little bit of a chance to talk about cancer screening. This is something I'm incredibly passionate about and it's something I love talking about with my patients. The show notes for this are going to be important because one, radiology is obviously a very visual field. You see things and much more than you sort of hear things. So we're going to do a great job to
pair a lot of what we discuss with images, especially once we get into the confusing MRI stuff and we try to explain the difference between a T1 weighted image and a T2 weighted image and a diffusion weighted image.
and things like that. The second thing is we're going to link to some of the material that we use with our patients on cancer screening, because I know this is a very controversial topic, and I suspect that this episode is going to generate just a lot of controversy, but I want to be clear that cancer screening is a very personal decision, and it comes with risks. And the biggest risk
of course, is a false positive, which then leads to subsequent screening, emotional distress, potential harm. We talk about all of this stuff. And as I said, we'll link to some of the materials that we've prepared specifically for our patients that I think just create a nice primer for how to go through that. So without further delay, please enjoy my conversation with Dr. Raj Atariwala.
Hey, Raj, thanks for carving some time out today in the middle of your busy day. I've probably done what no one else has done before, which is shut down this clinic, huh? That's fantastic to see you again and to be here. It's a pleasure as always. What's the deal with Vancouver and Uber? I got off the plane this morning and tried to get an Uber to come here, and apparently there's no Uber in Vancouver. It's stunning. Everybody complains. We all complain. But I don't know, somebody somewhere is not allowing it.
It was amazing. I was in India and you can get Uber in India. Yeah. And it's not a Canadian thing because I Ubered in Toronto. Toronto, Calgary, almost all the country, just Vancouver. Very well. I'll reserve my editorial comments for myself. Well, I've been looking forward to this for a long time, Raj. We've known each other for about four years. I think we were introduced through a mutual acquaintance who's a good friend of mine and has become very interested in your technology.
And I'm not even sure if you remember the context, but the context was basically this person reaching out to me to say, hey, there's this really fancy MRI scanner up in Vancouver. Can you go check it out for me? And at the time...
I was focusing a lot on different technologies that might be able to aid in the detection of atherosclerosis. And he may have misunderstood what I was interested in, but it was sort of pitched to me through that lens. You and I hopped on a call. I still remember where I was sitting actually in my office at the time. It was probably, yeah, it was in January.
By the end of that call, I was really interested. And you said, look, I mean, I think you should just come up to Vancouver, get scanned and let's spend a day discussing it. And the rest is history. So, you know, what I wanted to do today was obviously talk a lot about AIM, which is the, well, I guess it's the name. Is that the name of the company or is that? Yeah. So actually what I did is I actually set up AIM as a private MRI company and we basically put in the MRI machine so I could play with it. That's one of the problems of being an engineer. Yeah.
And so AIM is the name of the scanning company, the clinic.
but we've actually now kind of moved it into prenuvo. And what prenuvo is about is actually to basically sort of put the power of preventative medicine into patients' hands. Yeah, well, we'll talk a heck of a lot about this, but let's talk a little bit about your background because that was one of the things that right off the bat made me realize that this was going to be an interesting discussion. I, even in medical school, just took a huge interest in radiology. I never thought for a moment I would become a radiologist, but I knew that whatever type of medicine you practice,
you have a choice, which is basically you can just be confused and intimidated by all of these scans that your patients get, or you can at least try to understand them and have some hope of appreciating the risks of them, the benefits of them, the subtleties, et cetera. So when I did my radiology rotation, I was probably...
the most eager student who wasn't going into radiology. And I remember, and I still have my notes, but I took, I mean, maybe 50 pages of notes, drawing coils and all sorts of things. So let's start at the beginning. You have a background in engineering, which a lot of radiologists seem to have, right? It's actually common in radiology. It's like, basically there's a lot of technology in radiology. And so as a result, it attracts those of us who actually are technophiles.
And so my background, actually, I started out in chemical engineering. And then during that period of time, I kind of realized that I actually kind of like the body and physiology and how that works. And as a result, I then went into biomedical engineering where I did my master's and PhD in biomedical engineering in Northwestern. During that period of time, I was actually working on fluid mechanics. We're actually looking at blood flow and hemodynamics and all sorts of complicated things. And we also actually did what engineers do,
We actually had all these manual systems that we're using to measure blood flow and blood pressure. And we decided, okay, let's build a robot to do it instead. So we did. And this robot that we actually built allowed us to do keyhole surgery in the eye that wound up attracting a lot of attention from physicians from top tier universities all over the United States, from mass general everywhere. And as engineers, the attitude was we can build anything you want. What do you want?
A lot of times physicians can never answer that. I was working with a lot of these top tier guys, like editor in chief of the different medical journals and ophthalmology. And it was like they were speaking a different language and I just didn't understand what they were talking about. And so I actually kind of decided, okay, well, let me apply to medical school and see what happens so I can actually kind of learn this language and kind of learn more about medicine.
And so I applied and then I actually kind of got accepted. And I was like, hmm, do I want to do this? It's like, I'm really an engineer and was born an engineer. So my PhD advisor's famous last words were that the engineering world will always take you back. So I went off to medical school and actually hated every minute of it. It was kind of like,
I need to know more. I'm one of those kids who's kind of like, why, why, why, why, why? How does this work? Explain this to me. I don't get it. And realize that there's a lot of things in the body and physiology and pathophysiology that we just don't understand. Despite the massive amount of literature that's out there in the medical world, you really couldn't find a lot of the answers of why things go wrong and how they go wrong. So then I'd wind up sort of exploring, okay, how do we advance understanding of what's going on in the body? Like the simple aging process is
What happens? Why does everything change? Why? People can answer it. Instead, it was like, okay, memorize this list of changes. I'm like, okay, great. Let me try and remember all that.
And what I would actually start to boil down to is that I would actually go back to my engineering pathophysiology texts and I actually read them and talk to the PhD guys. And they would actually sort of give me the theories on what they thought was happening. And when you actually got that theory, it was almost like planting a seed. Then you actually kind of understood how the entire tree would look.
And that's when I said, okay, maybe this is good, but I still need my technology. Where is technology going? We worked on some of the very first surgical robotic machines ever built. My colleagues presented the first telerobotics telepresence conference ever held in the United States. At the same time, the group that made the DaVinci was there. I kind of looked and said, there's not a lot of space for robotics because people don't want machines built.
operating on them. As a former surgeon, I'm sure you probably feel the same way. You don't want a machine operating on you unless it's going to be better. So that's when I decided, okay, the technology that people understand, doctors understand is a picture and that picture is radiology. And that's really where all the technology is. And so I actually started in an area called nuclear medicine, which is a sort of a small specialty within radiology, which is where you're actually looking at functional imaging, how things work, how do things change, what happens over time,
And really enjoyed that area because it was sort of showing you what's happening when things are normal and then when things become abnormal. And it was actually one of these other amazing fields that in medicine, there's a lot of shades of gray, whereas in nuclear medicine, it's almost black and white. It's there or it's not. It's one of these very few areas where you actually get a binary choice of what's happening. Is there a problem? Yes or no. As opposed to, well, there might be.
So that's actually what I liked about it. But then I also kind of realized that radiology is basically very much like anatomy. You actually see what's going on. You actually see the changes and you see the shapes of things. And you use that very much as a blueprint for a building to actually kind of see what it does. Whereas nuclear medicine is kind of instead of the blueprint, you actually kind of know there's all these people carrying letters moving in and out of this building. We don't really know the detail of where the building walls are.
But we know that there must be something happening there. And hey, when you put the radiology with the architecture together of the blueprint of the building, then you combine that with the people going in and out of it, you realize it's the post office. And you realize that these are postal workers carrying things. And here's the geometry of the building.
So that power really is actually quite useful in the fact that it's really, there's this famous equation when people actually realized to put functional imaging or nuclear medicine imaging together. The first device that did that was positron emission tomography and CT or PET-CT. And the famous equation is that one plus one equals three. These two separate modalities of functional imaging and anatomic imaging come together to actually make something better than each part individually.
And so that's what really attracted me to the whole field, just because you could see what's going on and you can actually see the power of what's happening. That was certainly one of the more powerful lessons I remember as a medical student when I went sort of headlong into radiology, which was what I really liked about this rotation. I remember, I wish I could remember the names of the residents, but they took me under their wing, even though they knew I wasn't going to be a radiologist. And as you know, from being in medical school, that's a little unusual. Typically the residents tend to gravitate to the students that are going to follow in their footsteps. But
I think they saw in me a genuine curiosity and they thought, well, look, the smarter we can make this surgeon, the better down the line for us radiologists. And so I remember them taking me aside and saying, look, Peter, anytime you order a test in the back of your mind, you have to be asking yourself, do you want anatomical information or functional information or both? And the example you gave is a great one. And in the show notes for this podcast, we'll link to tons of pictures so that people understand what is meant by
And the way I would explain this to a person is an anatomic image has nice sharp edges. It looks like what it is you're trying to take a picture of. So the anatomic image of the brain shows all of the substructures. And when the radiologist looks at it, he or she can make out every little detail.
blip and bend and crevice inside of the brain and they can comment on different structures while there's a tumor here or there's a blood vessel that's slightly dilated there. If you contrast that with the PET scan, as you pointed out, that's looking at a function of the brain, which is how much glucose does it uptake? And instead it lights up darker, the more glucose that's being taken there. And that's, so in your analogy, the CT scan is showing the architecture of the post office, but the PET scan is
is showing you the distribution of people moving into different areas of it. And by putting it together, that gives you a really powerful picture. Exactly. And that's actually exactly how it works. And, you know, one of the things that might be useful as well is if we kind of look at the different sort of techniques that are used between nuclear medicine and radiology, we all know that imaging started with the simple x-ray.
But that was actually groundbreaking for the field of medicine. Well, let's start with that. So everybody has seen an x-ray. And I think most people, if they can close their eyes and picture it now or look at an image, kind of know directionally that an x-ray is nothing more than a series of contrasts going from black to white and everything in between. So
At the highest level, how do we take an x-ray? What are we doing with those little electrons going through someone? How does it produce that image? For sure. And it's quite amazing actually how it was discovered by Runt. And effectively what it is, is we're taking these high energy wavelength and it actually penetrates right through the body. And anywhere where there's something dense, very hard, like bone, the x-ray beam can't make it through. We've all sort of taken like a...
flashlight and sort of shown it through our finger and we can actually see the red light coming through. Well, effectively that's what an x-ray is. We're just taking higher energy wavelength that we can't see with our eyes. And it's actually allowing the areas where there's things like air or soft tissues, the x-ray penetrates right through it and goes right through, shines through. Whereas in places where there's bones, the x-rays can't make it through. So they actually get left behind. And that's what gives us like the white pictures of the bone because the film that's exposed on the other side is
soft tissues, the x-rays have gone through, they turn it from white to black, whereas in bones, the x-ray doesn't make it through because it gets left behind in the person, and therefore on the film on the other side, it stays white. And back in the days of Rankin, did they appreciate the damage of ionizing radiation, or were there a number of casualties along the way from people being far too exposed to this type of energy? Unfortunately, there were lots of casualties, and actually our understanding of radiation has actually
been moved by really traumatic events such as Hiroshima, Nagasaki and things like that where there's been real radiation damage and we've actually been able to watch people over time
And recently, in the past 10 to 15 years in imaging, we've actually realized the danger of this high-powered ionizing radiation and how it can damage cells. And when the DNA of the cells get damaged, there's a risk of inducing cancers with that. And so we're actually starting to understand that more and more. And we're actually starting to see that a lot of patients, individuals are like, look, I know about the potential damaging effects of x-ray radiation. Therefore, I don't want a lot of x-rays, CT-type scans. Yeah.
Now, the way I generally talk about this with my patients, I have a graph that I show them that on the x-axis lists a number of different technologies. So a chest x-ray, an abdominal x-ray, a mammogram, and they're generally in increasing amounts of radiation. So at the top end of that spectrum, you'd have a whole body PET CT just for if you want it to go as ionizing as possible.
And then the y-axis, I use these units called millisieverts. Can you explain what a millisievert is? Exactly. So a millisievert is actually the unit of measurement of radiation, and it's actually set by the standards group System International in France.
that actually sets what a standard dose of radiation is. And now it's actually important that a lot of people really don't understand radiation. There's good radiation, there's bad radiation, but radiation is any time you actually have any ion that's actually releasing a component of its energy, that energy has to get deposited somewhere. It actually comes off as a photon of energy that...
has to by, I guess, energy effects go from, it's never created, it's never destroyed, but it's actually transferred. And so that energy, if it doesn't go through you, it's actually going to deposit in you. And if it actually deposits in you, that's where it can actually cause the damage. And now when we look at all the different types of imaging, as you talked about, on one end, you have the mammogram, which actually has a very low amount of radiation in millisieverts. It's usually about 0.05, which is quite negligible.
Whereas on the other end of the scale, you'll have the PET-CT. And now the PET-CT basically couples the radiation from the CT. And the CT scanner is basically a powerful x-ray that's spinning around the body and creating a three-dimensional view of you.
combined with the PET, which is the positron emission tomography, where you're taking radioactive glucose and you're actually labeling with fluorine. And that fluorine is a radioactive fluorine 18, which actually now gives off a positron. And that positron has tremendous amount of energy. It's the highest energy that you can actually have in imaging for radiation. And that's 511 kiloelectron volts. So very, very high.
And so when you combine those two together, you wind up getting typically when we actually give somebody radioactive glucose for a whole body scan for, let's say they have cancer, it's roughly one millisievert per megabecquerel. But I guess I'm trying to convert the Canadian. Oh, that's okay. Yeah. We've got an international audience here. You don't have to make it Americanized. So we do it in megabecquerels up here in Canada. And so it's typically about 35 megabecquerels per millisievert.
So typically somebody will actually get the US dose would be about 12 millimoles. And so that's about the 12 millisieverts of radiation in addition to what they get on the CT scan. So they could easily get 30, 40 millisieverts in total in that scan if they were doing chest, abdomen, pelvis, for example.
It's possible, yeah. And a lot of that radiation would come from the CT. Whereas with nuclear medicine, what we typically do, since we're actually going to inject somebody with the radioactive material, as a result, we've exposed them to that radiation to all parts of the body. So as a result, as it circulates through their entire body, we want to take pictures of everything from head to foot.
Because if we're going to give somebody radiation, we want to maximize the amount of data we're going to extract from that exposure. Now, I don't know in Canada what the number is, but in the United States, the NRC recommends that no one receive more than 50 millisieverts in a year.
But of course, not all of that can be assigned to radiography because living at sea level exposes you to, what, two millisieverts a year, maybe three. I mean, I think even if you live at elevation, people in Denver are getting probably six or seven millisieverts a year at background. I'm probably a bit off on that. It might be a bit less. That's right. Yep. So the higher you go, actually get more cosmic radiation. And then as well, certain geographies will actually have radon, which is another exposure to the millisieverts.
And as well, when you actually travel, when you actually go up in altitude in planes, we actually get a lot more radiation exposure. So that's why pilots, for example, they actually, when they wear glasses, they actually have to block the UV radiation, the UVA, UVB, and also the x-ray radiation, which is much more prevalent at higher altitude. The route matters. I know I've calculated this for myself.
doing a lot of East West coast travel. Fortunately, not very much exposure. I believe it's less than 0.1 millisievert per round trip. But if you do LA over the pole, right, all of a sudden it goes up by, again, I don't want to misquote it because we have the data so I could just post it. But
it goes up by a nonlinear amount. It's much more radiation when you cross the North Pole than just the extra distance you travel. Exactly. And that's because of the ozone. The less ozone you have at the poles, the more exposure you're going to get because the ozone actually absorbs the radiation.
So there's actually a calculator available online for people to actually determine how much radiation they're getting from exposure. And it's actually required that pilots and flight attendants calculate their dose. We'll make sure we find that and link to that. I just, because the NRC says 50 is the limit, I...
I've never really thought of that as we should go up to 50. I've thought of that as they probably have some reason to believe that successive years with exposure to 50 millisieverts is not a good idea. Do we have a sense of what the implication of that is in terms of normal physiology? We do and we don't. And actually, a lot of the time, our understanding of that really comes from, like I said, the tragedies of Hiroshima and Nagasaki, as well as other people like in the Fuji reactor who actually got exposed. And that's where understanding of the damage comes from.
Now there's actually a landmark paper out of Columbia that actually looked at the amount of radiation that people actually receive from CT scanners and it actually forced radiology as a field to actually look at the potential damaging effect of x-ray radiation.
And what they actually kind of found is that the younger you are, the greater the risk of cancer induction from CT scanners, which is why in the pediatric world, we actually try and really minimize the amount of dose that children in particular are getting. And the sex as well matters. So females are actually more sensitive to radiation than men. Meaning if you took a 20-year-old male and a 20-year-old female, so both in their reproductive prime, are you saying that the
ovaries of the woman are more sensitive to DNA damage in the egg than the sperm are in the testes of the male? Exactly. I didn't know that. Why is that? And that actually has to do with the fact that the egg was actually produced during embryonic stage. And as a result, that DNA is effectively frozen in time.
And so as women are getting older and older, they're releasing these DNA in the eggs. So therefore, the younger you are, the fresher the DNA, whereas, you know, when they're prime sort of around 12, which is when this DNA comes out of the, I guess, frozen state during the beginning of menstruation.
that's when these eggs start to be released. So actually 12 is sort of the worst time for females. Which is really sad because of course anybody who's spent time in a hospital knows that there are invariably kids that need to undergo radiographic studies. They only need to spend a few days in a cancer ward to realize all these poor children that are right at that age and they're being exposed to it and
Unfortunately, there's not much of a choice. And trauma is another area where the child comes in having sustained a bad injury in a car accident. You go out of your way to use ultrasound whenever possible, but invariably sometimes patients do require x-ray and CT radiographic study. So let's go back to the x-ray because I like x-rays.
I like where you started there historically. And then you alluded to the fact that basically if you understand how an x-ray works, if you truly understand what's happening, then you understand what a CT scan is doing because it's just doing it in three dimensions spirally. So the other thing about x-ray that I think is very interesting for anyone who spends time looking at it just to appreciate it, even though it seems so simple, is nothing in the body is two-dimensional.
So you talked about how this photon is going through the body and if it hits a rib, well, that's going to show up as white. Whereas if it's passing through the lung between the ribs, it's going to show up as black. But of course you could hit a rib on the front, but not on the back. You can hit a rib on the back and not on the front. You can hit the sternum. So when you look at an x-ray, even to this day, I'm still constantly amazed at what the collage looks like of overlapping layers of tissue.
And I mean, I just don't think I ever got good at reading x-rays. It was actually easier for me to, I think, because we just spent more time reading CT scans and there's so much more anatomic detail. But when I look at these old time radiologists look at x-rays and the stuff that they could pull out of it, I was blown away. Exactly. It's true. It's an amazing skill to actually be able to pull that 3D information out of a 2D picture.
And if we actually kind of think about it, our brain is designed to always imagine in 3D, always think in 3D. You know, even if you actually, somebody lost an eye, they can still see in 3D. And that actually has to do with the fact that that's how our brain was wired or I was wired. And so,
The amount of information in x-ray is phenomenal, but the biggest problem is that sometimes you're actually overlapping different things and you just can't see. So quite often, the reason we do two x-rays, when you do a chest x-ray, you do a frontal, a PA, as well as a lateral, is so you can actually try and mimic those two together to become a three-dimensional object.
And so when CT came around, that's when it actually really allowed us to look at things in 3D. And that's where surgeons and everybody else who actually operates and deals with people in 3D, they can actually start to look at these and actually start to imagine what they're going to be operating on. They actually kind of get the power of where the 3D image comes in. And so a simple way to think about an x-ray, as I try to tell people, it's almost like an x-ray is basically like a flash. Take a single flash and you get a picture.
Whereas a CT scan is really like a searchlight in a boat kind of going around an island. You actually get all the images the whole way around. And then the equipment, what it does, it actually sort of sees how the intensity passes through, let's say, two panes of glass and comes out the other side. And then you can actually start to evaluate what's going on inside that entire building. The police officers use this all the time when they actually need to stake out a building or a site. They actually use it to determine where the occupants are.
And that's exactly what an X-ray does. It's triangulation effectively by spinning around in multiple different cycles by going around 360 degrees. So we
We should clarify our semantics for people. We use the term CT very loosely, but it stands for commuted tomography. And sometimes people back in the old days used to refer to it as CAT scan or C-A-T. And the A was for axial, of course, because it's going up and down the axial dimension of the person. Right. When was the first CT scan put into clinical practice? I mean, would it have been in the early 80s or something like that or earlier? Earlier than that, it was actually EMI, the phonographic company that actually built the very first CT or CAT scanner.
And I believe it was in the 70s or even earlier. It's actually been around for quite a while. Realistically, that three-dimensional image really revolutionized medicine, as did all imaging. And the other thing that people will often hear about, and I guess maybe patients don't hear about it as often, but it certainly gets touted to them as a feature, is they talk about the speed of these things. They say this is this many bits or that many bits. And
Presumably the first one was a four bit. I think it was actually even less than that. It might have been two bit and actually just took a long time to go around. And it was actually first used in the brain. So let's explain what that means. So two bit means you really only have two flashlights. Exactly. Or one flashlight, one detector. Exactly. Yeah. It'll be easier, I think, when people look at pictures and we'll make this clear. But you have this cylinder that goes around the patient who's laying down. And there's one place where you shine light.
the ionizing radiation and on the backside of the cylinder is where you read it.
And then that thing has to rotate. So it's moving in its rotational plane, but also moving up and down the Z plane in time, correct? Right. This makes so much more sense when I can use my hands, by the way. And so it's exactly like that. Basically 180 degrees apart, you have the x-ray and the detector, and then it actually starts to spin around in rapid revolution. So when you actually look at a machine, there's the donut hole in the middle, but
But around it, there's actually the casing and these two parts, the detector and the machine that are actually spinning around the body very, very quickly. It's actually quite fascinating. Maybe we can find a picture of one of these actually with the cover off. Yeah, we'll find one. And I feel like even when I got to residency, which is, so let's just say directionally 20 years ago.
I mean, I still think people were using 16 and 32-bit scanners, right? Yeah, they were. So 16-bit means you've got eight, you're spaced out equally eight units, and then you've got your eight detecting surfaces. Right. And so what it winds up doing is, so if you start at, let's say, the top of your head and go to the bottom, we'll call that the axial dimension, what the eight-bit would mean is that, or eight-slice, I guess is probably the more correct term,
is that you basically have like one slice and then you're actually measuring immediately below it and immediately below that. And so as a result, as you're circulating around the person or the patient,
you're actually doing eight slices at a time or 16 slices at a time or 32 slices at a time. So what that means is as you're rotating around, the amount of coverage you get is more the higher the number of slices, or you can actually also have thinner and thinner slices. And the more thin you get, the more detail you can get from an imaging perspective.
but the more radiation you require to overcome the signal and the noise background. Yeah. So what you're trading off is an optimization problem, which is speed, resolution, radiation. Now, where are we today? I assume 256 is pretty common. 256 is one of the common ones that's actually used for things that are rapidly moving, typically the heart. The heart. Do we have a 512 yet? In research. Really? Yeah. You can actually make them as high as you want. The problem is you eventually sort of get to these diminishing returns of how
than the slices are and how many images you need. So if someone needed to scan a part of the body with a CT scan that wasn't moving functionally, so something that's anatomically complicated like the pancreas, but it's not moving like the heart, are you good enough at 128 or 64? Like does 256 offer an advantage? It doesn't really offer any advantage, no. You can actually, eight slices work quite
quite well. As long as the person can hold their breath and there's not a lot of movement, eight slices work well. One of the things I remember at Hopkins, there was a radiologist there. I don't know if he's still there. I think his name was Elliot Fishman. And he was sort of the god of pancreatic reconstruction. And of course, this was important at Hopkins because at the time, Hopkins was the epicenter of pancreatic cancer surgery.
And as important as it was to have a great surgeon, John Cameron, Charlie O, et cetera, that could do this operation, it was as important to have an exceptional radiologist. Because as you know, and maybe some of the listeners know, many patients with pancreatic cancer technically shouldn't be operated on. And you'd really like to know that before you enter the patient's abdomen, which is not always possible. But I remember that Elliot Fishman's
He would have these 3D reconstructions of the pancreas at a time. I mean, today that's pretty common, but at the time, like nobody was contemplating this kind of resolution. And we would sit there on rounds and look at these images when they were still printed out on that sort of vellum, whatever the hell that plastic paper is. And you just couldn't believe it. So to think that he was doing that with relatively few slices, right? Exactly. And like the whole power of that is, again, as I mentioned at the very beginning, is that our brain thinks in 3D.
And so the power of that, as opposed to looking slice by slice at a 2D image, became very useful because now it became real. It became what our eyes could see, what our brains could see, and it actually really helped everybody plan their surgery. And so it really was revolutionary to actually start to look at things in three dimensions. Now there's another element that we're going to introduce to this, which is contrast. So what is contrast? Why do we use it? What contrast is, and for the CT world, it's actually an iodinated material that
And so what iodine does, it actually absorbs the photons and so therefore makes things look white on a CT scan. So it's like having liquid bone in your bloodstream. Pretty much, a liquid photon absorber. And so what it does is we actually inject it into the vein and then we actually, the heart pumps it around. And so that means we're actually able to time when we actually take the CT image in order to be able to see what type of organ we're looking for.
So you can think of it if you actually get the arterial phase, you'll actually see where the arteries are connecting to an organ, or else you can wait for the venous phase or when the veins are returning blood flow from that organ, and you actually see the entire detail of the organ.
And what contrast really is, is basically a way to light up the blood vessels and light up the capillary net and everything in between, between the artery and the vein to allow us to see the anatomic detail from the perspective of adding blood to it. And the name of course explains exactly why it's to create contrast. Exactly. In the absence of contrast, blood looks functionally like water. I
I feel like I just want to go into this in so much detail, but I'm also trying to be mindful of not going deeper than we need to. But I guess we can talk about a Hounsfield unit because that will allow us to explain this contrast thing and tissue differences, right? Exactly. So what actually happened in CT is that Hounsfield came along and kind of said, okay, how do we calibrate this?
And so there's a range of Hounfield units from minus 1,000, zero to 2,000. And what that actually has to do with is density. And so zero is defined as water. 1,000 is basically air.
And so as a result, we can actually see the difference between the density of bone and air with water effectively in the middle. So you have at plus 1000, it is black. Right. At minus 1000, it is pure white. Pretty much, yeah. And the biggest problem is that the eye actually can't see that range. So on our computers, we actually will narrow down and look at, we'll actually look at the higher Hounsfield units and we'll actually see lung. Then we go down, we look at the denser material.
and that becomes bone, but we can't see the whole thing. Right, so you could technically specify...
multiple parameters. You could specify the width of your window and where it is centered, for example. So if you wanted to look at lung, you would center it much closer to positive numbers and you don't need a very wide range, do you? No, not at all. So what's a typical lung window? Like 800 plus or minus 100 or something to that? I mean, I have no idea. I don't even remember anymore, but that's the gist of it, right? Exactly. Yeah. And actually, I don't even remember because you push a preset. Yeah.
And once you set it, you never really change it much. So I had committed all of these to memory in medical school. I was so obsessed with knowing the window for optimizing the viewing of every tissue. As did I. And then when you actually start to practically use it, you kind of, you wing it because what happens is that every person is actually slightly different appreciation for contrast. Yeah. And also it's like the amount of photons lost based on the patient's body size, the amount of absorption changes things. So the numbers actually kind of move around and
you wind up building a database in your mind of actually what you're looking at. And so when you first start, you actually push the buttons and it's like 60, 40 for the abdomen and you actually know all these numbers. And then as you kind of go through, you're like, no, I just need to see what I need to see. What you said a moment ago, it really brought back those memories of
How horrible it looked if you tried to set the window to be the entire plus minus 1000, you could appreciate nothing. And that sort of struck me as a metaphor for life at times, which is like at a thousand feet. Sometimes you can tell I'm looking at a human, but that was about that was about the limits of detection. But you could appreciate so many different things by seeing.
zeroing in on the capillaries of the lung, but you had to be in the right resolution versus if you wanted to look and see if they actually had a fracture. People forget CTs are great for bones, right? And we're going to talk about how MRI, for example, is less great for bones. So now we've got the CT thing. So what we've established is that
X-ray is a purely anatomic study. There's nothing functional about it. As you go into CT by itself, it's also a very anatomic study. You can add contrast to get even better information about the vasculature. And you now have so much information that you can
basically titrate or calibrate the window in which you look into that collection of radiation and specify your tissues. CT scans are generally pretty quick, right? People who are claustrophobic don't tend to struggle that much in a CT scanner, correct? Exactly. And that's actually the real power of CT is the speed. So for example, in trauma settings, that's what you want.
Basically, if a patient's not doing well in a trauma, you want to put them through the CT scanner as fast as possible to get the information out as fast as possible. And they're very fast. So something that's even faster than CT and comes without at least one of its most significant drawbacks, which is radiation, is ultrasound. So how does ultrasound work? Where does it fit into this? And what are its limitations? The way ultrasound works is basically it's a high frequency, so higher than what our
And effectively it's penetrating solid tissue. So it's a high frequency sound wave versus an ionizing wave of energy. Exactly. And so then it's actually going at every tissue interface, it actually reflects back. So it's very much like an echo. So if you're standing in a mountain range and you yell out, you actually hear the echo coming back. And you can actually, from that time, you can determine how deep that tissue is.
And so with ultrasound, we're just doing that very, very fast. And so at every tissue interface or every mountain range, if we could, you actually hear that reflection coming back. You actually are able to then composite that as a representative of how deep things are away from you. Now, there are...
animals that do this, right? Including some of our closest relatives, right? They do. And as bats also do them, that's actually how they see. And the bat's resolution on this is what compared to say a dolphin. I've read, and I feel like I read this in the journal science many years ago, so I'm almost assuredly not remembering this correctly, that the resolution with which
a whale or a dolphin could undergo sonography rivaled that of our finest medical equipment. I mean, their ability to discern was remarkable. I found that amazing. And of course, in part, that's because they're the medium through which they travel is water as opposed to what the bat has to do, which is go through this poorly, poorly dense air, right? Exactly. So traveling through the different material actually makes a very good way to explain it because in the air,
Actually, ultrasound doesn't penetrate very far because it's as high frequency and it just, you lose it because there's no reflection coming back.
Whereas in more solid material like water or even dense material like organs in the body, it actually reflects back easier. And so it's actually that reflection that actually allows you to discern the different tissue types based on how quickly it reflects back. Now, ultrasound can't harm you, right? You don't have ionized. You could ultrasound yourself all day, every day for the rest of your life, and you're not increasing your risk of cancer. Whereas if you did a CT scan of yourself every month...
you're going to be in trouble after several months. Exactly. The drawback of ultrasound is the resolution doesn't seem to be as high. Right. With ultrasound, you're only looking at one slice, right? So you're only looking at one slice in time and you're basically kind of sweeping through an organ, trying to composite those slices together in your brain to try and build that 3D model.
Because like I said, our brain always wants to build a 3D model. So with ultrasound, as you sweep through, you get one layer, then you get another layer, then you get another layer, and then eventually that's composited together to see what's going on. And ultrasound also seems to really struggle when it encounters air inside the body. So...
If you're trying to do an ultrasound of someone's aorta, but their bowel is in front of it, it becomes difficult to see for the same reason the bat can't really use high frequency ultrasound to fly. Exactly. And so that's why when, for example, you look at a female pelvis, you want their bladder to be full because in their bladder being full of fluid, it actually acts as a nice window to allow the ultrasound beam to pass right through to be able to see the uterus behind it. Right.
I think any woman listening to this who's been pregnant, that's got to be one of their most vexing parts of prenatal ultrasound is they always had to sit there in a waiting room with a full bladder waiting to have that ultrasound. And of course, that's why we like to do ultrasound on a fetus, right? Is you're not causing any harm. I mean, certainly one thing I came to appreciate in the hospital.
Was the skill that was required on the part of the person doing it? So if you gave me the best ultrasound device money could buy today like you literally when bought whatever ultrasound Was at the absolute limit of technology and then you walk down to the local hospital here Vancouver General and you grabbed just a middle-of-the-road radio radiology ultrasound tech someone who's maybe been out of school for a year and
and you gave him or her the worst ultrasound machine on the market, there's no comparison. Who would be able to see more? This is where skill and experience is invaluable. Basically also dealing with the difficult patient body type is really critical and you can't replace that experience. Now there's a special subset of ultrasound that we do on the heart.
Where did that idea come about? Who figured that idea out? Again, the value was like once you could actually find like a nice window that would actually allow you to miss the air in the lungs and actually kind of look at the heart, you realize that, boy, you can actually start to see this two-dimensional plane of the heart quite well. And as a result, you can actually see where things were moving such as the valves in the heart or the walls of the heart moving.
And then as well, you actually add something called Doppler, which is basically the frequency bouncing off of blood vessel. If it's going or coming, the frequency is going to be different. And so as a result, you can actually now start to see how blood is moving. And so that's what Echo does. And so it actually allows you to look at the heart in detail with a very, very thin window, usually underneath blood.
the chest and around the lung. Yeah. So anybody listening to this, who's had an echocardiogram, they know that the person doing it is really pressing quite hard. It's somewhat uncomfortable for you, the person getting the echo done and
And the reason is they've got that jelly on you, which again is doing everything to eliminate even a drop of air between the interface. And secondly, they're pushing and they're grinding it in between the ribs and they want to get that view versus, so that's a trans thoracic echo where you're doing it over the chest. In surgery, often if we needed to look at the heart, you would add the anesthesiologist would actually put the echocardiogram in the esophagus.
and you get an even better view of the heart. The esophagus sits right underneath it, and there's nothing in between. It's a beautiful view, and the patient, obviously, because they're asleep, they don't have to worry about having this huge probe stuck in their esophagus. Right, and because you're closer to the organ you want to see, being the heart, the details can be fantastic, because one of the other things with ultrasound is that
the deeper you go, the beam effectively fans out and gets thinner and thinner. So you actually get less sort of detail on the edges. Whereas right in the center, right underneath the probe is where your maximum amount of detail is going to be. So by having it right in the esophagus, which is right beside the heart, you're going to get fantastic detail. As important as the CT scanner was in trauma, the ultrasound was actually the most important radiographic tool we had in trauma. And that was the one thing that even the surgical residents needed to know how to do.
And it was called a fast ultrasound. There was an algorithm for this because in a busy trauma center like Hopkins, you're going to see trauma so often, penetrating trauma in particular, where you have to know, does this person need to go up to surgery? Is there fluid in the abdominal cavity? That's generally one of the things you care about. You certainly also care if there's fluid around the
the pericardium, this non-stretchy sac that surrounds the heart. These are surgical emergencies, especially fluid around the pericardium. So I think sometime in our second year of residency, we would go off and do this course where on pigs, we would have to practice this over and over again until you learn the four places that you were looking for fluid inside the abdomen. I guess we got pretty good at it. I think I got okay at it, but I still always felt like
little nervous when push came to shove because I always felt like I wish I could go and spend a year just being an ultrasound tech to really really dial this in because the stakes are so high especially if you miss the slight amount of fluid in the pericardium that's a lethal injury and one of the real tricks as well is that depending on the composition of the fluid there's like frank blood or coagulating blood it can be really tricky to actually pick it out and so a lot of times you'd actually see the fast ultrasound would be done and
And if people weren't 100% confident that there's a problem or not a problem, they go straight to CT scan because you just couldn't make that error. And that happens time and time again. Yeah. And it's funny. One of the last traumas I was ever involved in as a resident was just one of those cases where
The patient came in and he was responsive. He had the tiniest, tiniest stab wound. So less than a centimeter wide under the xiphoid. That's it. So this is a guy who walks in who has a sub centimeter sub xiphoid incision. I mean, it could have been a shaving cut.
but he's been stabbed and he's more or less seems pretty normal. Vital signs are more or less what you would expect. When I lay him down and do this ultrasound of his heart, it really looks like there's something there, but I can't quite figure it out. And now the question is, well, he's obviously too responsive to warrant cutting his chest open, which was what you would do in the emergency situation.
So you have to do the CT scan. But of course, the risk in the CT scanner is as fast as the CT scanner is, he is still laying down on a scanner, potentially ready to have a cardiac arrest and
for at least a minute and a half. And usually what would happen is, I don't recall in this case, but a lot of times if you're going to go through the trouble of doing that, you're going to do a contrast CT scan as well. You're not just going to do what we would call a dry scan with no contrast. So now you've got the fumbling around of getting the iodine machine hooked up to him, et cetera, et cetera. And Eddie Cornwell, who was the chairman of surgery at Hopkins, he's now the chairman of surgery at Howard and just an incredible human being. I remember one of the things that he told us when we were junior residents is,
beware of the patient who gets wildly anxious when you lay them down. And sure enough, when we go and lay this guy down in the scanner, he just starts freaking out. And when you sat him up, he sort of calmed down a little bit. It was do not pass go, do not collect $200 and took him to the OR, opened him up immediately. And sure enough, that knife had actually hit his pulmonary vein
And so that pulmonary vein was bleeding into his pericardium. And so he would have had a cardiac tamponade if we'd left him on that table. And amazingly, that patient went home three days later. Yeah, no, exactly. And you can see like the power of the clinical skill as well as like just the basic imaging, right? The power of imaging plus clinical is pretty much where medicine is right now and how we actually are able to diagnose things quickly and efficiently. So we've talked about two technologies that most women are very familiar with when it
of the cancers where screening is done vis-a-vis imaging technology, breast cancer is head and shoulders above the others in terms of the frequency and ubiquity of the scan. So let's talk a little bit about, because you've already explained what an ultrasound and an x-ray is, so now explain what mammography is and why we would sometimes say mammography is sufficient versus insufficient, and why do some women get told, well, you also need an ultrasound? Right. So basically mammography is a
lower attenuation x-ray. We're actually taking x-ray but a weaker strength of it because we never have to penetrate bone and actually now it shines through the breast tissue which is all soft tissue. And so one of the things that actually is maybe stepping back is to actually kind of look at breast tissue in particular. So breast tissue is composed of normal subcutaneous tissue which is mainly fat and as well as glandular tissue and
And so when women are in their childbearing age, it's almost all glandular tissue to produce milk for eventually feeding a baby. And as women then go through menopause, that glandular tissue can invariably involute. So it's one of these things you don't use it, it gets replaced with fat. But in some women, it actually doesn't get replaced with fat. And that is what we call the dense breast tissue problem.
So mammograms are very, very good at shining through fat. And it actually allows you to see very, very simple things like calcification in fat because they are just so dense and it actually just stands out. Whereas in glandular tissue, sometimes that photon of low energy x-ray doesn't make it through. And as a result, the tissue is very, very hard to see through. And that's what we call the dense breast tissue. And the reason it's hard to see through is because of all that glandular tissue that in some women...
over menopause or even older, they just retain. Nobody really knows why they retain that extra glandular tissue. Why in some women it gets replaced with fat, in other women it doesn't. We don't know why. And so many states, and I think they're actually over 38 and possibly soon to become a federal law in the United States, is going to require that the very first line on a mammogram report is going to be that the women's breast tissue is dense, limiting mammographic sensitivity.
or the breast tissue is almost entirely fat, in which case mammograms are helpful. Because that actually will really allow women to determine, was this test good enough?
And so for women who actually have dense breast tissue, so they, for some reason, if they're postmenopausal or if they're premenopausal in their childbearing age, they still have a lot of glandular tissue. That means a mammogram might not be enough and therefore they need another second imaging modality to look through the tissue. And that's where ultrasound comes in. And as well as MRI would come in as well to be able to see through that dense glandular tissue that the mammogram can't see through. Now, the last time I looked and these data could be, they could just be simply dated, but I think directionally this is right.
A mammogram had a sensitivity of about 80, call it 84, 85% and a specificity of about 90, 91%. Does that still sound about right to you? It depends actually. Yeah. That was like all comers was the point I was going to make, which is it becomes almost impossible to interpret what that means because
Because what you need to know is what if I had a thousand women that looked exactly like the women I'm scanning right now? Exactly. And so that's where it actually becomes really critical. And the fact that depending on the breast density, and that's why it's important for women to know what that is, you're going to know how helpful the mammogram is or may not be. But one of the other things that becomes actually very, very powerful in the mammogram is to actually use comparison over time. So
So that's why they recommend screening intervals of either one or two years. And it's a matter of academic debate. And because if you actually have like a mammogram taken, and then let's say two years later, you do another one.
It's actually far more sensitive to see that subtle change over time than it is to actually look at an individual mammogram all on its own. So a single mammogram on a dense woman, its sensitivity is about 55%. It's actually quite poor. Whereas on a woman who actually has fatty tissue, it's very high. How high? It can actually be over 95%. So let me explain what sensitivity and specificity mean so that a person understands what this is about. Let's just use the numbers 80 and 90 because those are generally accepted numbers.
So when we say a mammogram has an 80% sensitivity, here's what we mean. If there are a hundred women who have breast cancer, so there's a hundred women and we absolutely know that they have breast cancer and we subject them to a mammogram.
80 of them will test positive. 80 of them will have a true positive and 20 of them will test falsely negative. So the sensitivity is the true positive rate over the true positives plus the false negatives. Correct? Exactly. So the higher the sensitivity is,
the less likely you are to take someone who has the cancer and miss them. That's the juice on sensitivity. Let's now talk about specificity. So mammography, a moment ago, you gave a staggeringly sad example. So we'll come back to that, but let's use the better one, right? Let's say 90%. So now what does it mean to have 90% specificity? So that means you take a hundred women who we absolutely know do not have breast cancer.
and you scan them. 90 of them will correctly identify as not having breast cancer.
10 of them will incorrectly identify as having breast cancer. So 10 will be false positives. 90 will be true negatives. So the sensitivity is the number of true negatives over the true negatives plus the false positives. And so the example you gave a moment ago is if you have a woman whose breasts are very fatty, not glandular, therefore she's the poster child for mammography,
you're driving that specificity up, which means you are reducing the number of false positives. But in the example you gave earlier, which is a woman who might have very, very dense breast tissue, imagine what it means to take 100 women who have very, very dense breast tissue and drive your specificity down to 50%.
That means on a given day, half the women that walk into your clinic are going to be told they have cancer if they don't. Exactly. So it's like flipping a coin. And by the way, one of the greatest examples of this, and I mean, I attribute it to Bob Kaplan, but maybe he heard it somewhere else, but I love it, is you can make a test that is 100% sensitive.
If you're willing to have 0% specificity and vice versa, for example, you could send a letter. You could have a little card that says you have cancer and you show it to every single person you meet. You have a hundred percent sensitivity.
right? Right. You will never have a false negative. The problem is that's so clinically useless because you have no specificity. And similarly, you could have a little magic card that you show everyone you ever meet for the rest of your life that says you do not have cancer. Guess what? You have a 100% specific test. It just has zero sensitivity. So it's as useful as a warm bucket of hamster vomit. And
And so it's this trade-off between sensitivity and specificity, which I'm teeing this up because I know we're going to come and talk about this when we get into the more advanced MRI stuff. But the example of mammography is amazing to me because it makes you realize you can't just rely on one test, especially when that test has such low sensitivity and specificity depending on the individual. Exactly. And I think that that's the real important lesson is that it's actually very individually tailored, right? And so if you have one test,
and you don't know what your fingerprint or what the tissue that your breast is made of, you really have no idea what you're looking for. So you always need the one to kind of find out, is this good enough? People always talk about machine learning and AI and how invariably it has to infiltrate medicine. And it seems to me that one of the best places for it to do so is in at least comparative radiology. So
Given the ubiquity of mammograms, hopefully every woman above a certain age in the United States, Canada is getting regular mammography. There's no shortage of data. Are there companies out there that are working on basically doing that once you have a baseline, which would be almost impossible for a machine to read, but once you have that baseline longitudinally comparing it? There are actually a lot of companies that are actually doing that. And
And even in some states that are actually using machine learning techniques to actually help the radiologist and they actually can be used as even a second reader. There are a fair number of companies working on that, but it's not perfect. What do you think that could improve the sensitivities and specificities of mammography to? I mean, can we get to the point where, I don't know, I mean, most people would say you've got to be north of
97, 98% on both to really feel confident. I think that's a pretty high target to achieve. And the reason that would be is just because of the way the tests are done and the individual variability of people. It's going to be tough. Can machine learning get that good? It'll take a while. It's going to need volumes and volumes of data that's actually reproduced the exact same way. And I think that's the biggest problem is because we're unique and
The way the breast is compressed, the way everything is done when a mammogram is taken is somewhat different each time. So the amount of coverage is a little bit different each time.
It's possible. Are we there yet? No, we're nowhere near close, but we're getting better. And that's also one of the challenges that we have when we look at the data on mammography is it's so backwards looking. And so if you want to look at the most comprehensive study of mammography and breast cancer screening, by definition, you are looking at a trial that was enrolling patients 15 to 20 years ago and therefore unrecognizable.
You have to be able to say, well, how relevant is the technology that was being used then relative to today? And in the case of mammography, it shouldn't be changing that much. But I mean, things do get better. I mean, we're reading pure digital now. We have much better capacity to read even an x-ray than we did 20 years ago, don't we? We do. And basically now what's actually happening is we're actually doing a fluoroscopic version of a mammogram where we're basically sort of trying to slice through this three-dimensional object and
and actually get the detail of it at a three-dimensional layer. Whereas before, the mammogram were typically just like the chest X-ray was done, two different views compositing that three-dimensional picture together.
So that three-dimensional view of the mammogram is actually better than it was. Now, there's something else that I've never actually seen done clinically, but I've read about it called MBI, molecular breast imaging. Is that used any longer? And what is it? The reason it came across my radar was many years ago when I was just trying to get the landscape on ionizing radiation. This came up as a test that was done as a follow-up to a mammogram. But I
I thought there must be a typo based on how much it had like something like 20 millisieverts of radiation. I mean, it was 40% of your annual radiation limit. What that is now, that's a functional test. So in the realm of nuclear medicine. And so what that is doing is we're actually taking radioactive material and then we're actually injecting it into the body. And so tissues that actually have increased mitochondria actually concentrate this radio tracer.
And so that typically happens in breast cancer. So it's actually used with a radiotracer called SestaMib. You've heard of this MIBI scan, which is where we actually inject this into the heart. And we actually look at whether or not the heart is being properly perfused.
And so areas that aren't being perfused, so therefore the muscle is not alive, basically don't take up the radio tracer. Whereas muscle that is alive does take up the radio tracer. And that muscle that's alive, that's moving, has a very high mitochondrial rate. So therefore it actually concentrates this material. So breast cancer was actually doing a very similar thing. They'd actually have a high metabolism and
And so this tissue would actually concentrate, or this radiotracer would concentrate in that tissue. So that was the MPI exam for breast. Is that test still done? Rarely, but it can be done in women who actually have very, very dense breast tissue and you actually need to see what's going on. It can be done, but a lot of it's actually been replaced with positron emission tomography scans. So right now, how many women, young women, if we just say because the young women are going to be more likely to have dense breast tissue, do we have a sense of what percentage of them really are being...
uncovered, meaning they're not getting adequate sort of surveillance with just mammography and would require at least ultrasound. Is that a third of women? I mean, do we have a sense of what that number is? Depending on the jurisdiction. So the guideline for when you actually start screening for mammography can either be for the age of 40 and higher or 50 and higher. Each jurisdiction is a little bit different.
So what that means is that basically anybody under the age of 40, unless you have a family history of somebody having breast cancer at an early age, they're not getting screened at all. So everything we've talked about from a technology standpoint in some ways pales in comparison to what we're about to talk about, which...
is about as complicated a set of physics as you're going to find within the walls of a hospital, right? I mean, it doesn't get a lot more complicated than an MRI, does it? No, it doesn't. It's really an engineer at delight. Yeah. And I certainly, again, thinking back to my brief six weeks of doing radiology, I feel like more of my notes were scribbling down an explanation of how this thing worked than anything else. So
Let's go back to the beginning. Who the heck thought of this? There were actually three people who actually thought about it, but Mansfield is actually one of the main creators of it in the UK. And so the MRI machine, really, it's actually quite an amazing tool. And it actually wasn't initially developed for imaging. It was actually just sort of developed on a benchtop where they're actually just kind of looking to see what the effect of
electromagnetic waves does to anything and somebody wind up sticking tissue in it saying hey look it's like we can actually what goes in one side comes out a little bit differently on the other side
And as a result, we can actually determine what that composition of material was. So does that mean like the NMR that we were looking at when we did organic chemistry was really the precursor to the MRI that we're sitting outside of right now listening to at home? It's the exact same device. The NMR basically is just a two-dimensional version of an MRI, which is three dimensions because our brain likes three dimensions. So let's go back to organic chemistry. So again, we'll link to a picture of...
an NMR spec so that people can see what we're talking about. But I guess there's also no easy way around this, right? I think you have to sort of roll your sleeves up a little bit on physics to understand how an MRI works. There is no, I'm sure there's a kid's book out there waiting to be written on the topic, which would be amazing, but it's pretty tough. So you take a molecule like
alcohol. Okay, so it's got these two carbons that are joined. The first carbon has three hydrogens around it. The next carbon has a hydrogen and a hydrogen, but then instead of the third hydrogen, it gets an oxygen which is bound to a hydrogen. That is the stuff that people drink and get drunk on. Now,
Put that into a nuclear magnetic resonance machine and you're going to see different peaks, right? It's going to show you that there is a methyl group somewhere. It's going to say, it can't tell you what it sees, but it tells you that there's a carbon bound to three hydrogens, right? Right. How does it do that? Perhaps I might actually take up the challenge of a children's book. Problem is I dislike writing, but maybe for children I'll be okay.
The way it actually does it is actually quite fascinating, and it's actually relatively simple. So what it actually does is the hydrogen in particular, so we're going to sort of fixate on hydrogen because that's the atom that we're really interested in. And I'm just going to say one thing because you're going to do this anyway, and I just want to preface it. You're going to use hydrogen and proton interchangeably, aren't you? I will. Can you just tell someone why you're going to use hydrogen and proton interchangeably? Sure. So the atom basically of the hydrogen is you have...
one proton and one electron. And in the hydrogen proton, we don't really care about the electron. It just sort of disappears. So the hydrogen proton
I guess nucleus is a proton. And it has no neutron. Its mass is one. Its mass is determined by the one and only proton it carries, correct? Exactly. Okay. So now hydrogen and proton, they're the same thing for the purpose of this discussion. Exactly. So when we look at the NMR, so you actually have hydrogen bound to an oxygen or hydrogen bound to a carbon. And so the behavior of that nucleus is going to be a little different. So there's basically a magnet-
That's creating a field and somehow through that we can see how the hydrogen is bonded to either the oxygen or the carbon in the ethanol molecule. Right. So we were talking about the NMR. And so what the NMR does is that it really is a hydrogen or proton imager or actually just detector. And so the way the magnetic field works,
of hydrogen behaves, if it's attached to either the oxygen and OH of alcohol or the CH3 of carbon, is completely different. It actually gives off a different wavelength. And so as a result, that's how we're actually able to get this, what we call NMR spectra. And so what happened is that from there, there's a person named Damadian, who many consider to be the father of MRI. And
He actually said, well, you know, look, if we can actually take what Mansfield and Lauterberg did on a benchtop, can we actually put a human in it and actually start to see the soft tissue? Because we know that our body's composed of roughly 70% water. There's a lot of hydrogen on fats. So can we see that frequency difference? We can see it on a benchtop, but what about in people? So we have more hydrogen in us. If we were just going to count up the atoms in us, hydrogen wins all day long. Because as you said, if we're 70% water, that's two to one
hydrogen over oxygen there. And then all the fat that's in us is all the hydrogen to the carbon there. And there's basically hydrogen in protein as well. I mean, so...
If you have a hydrogen detector, that's basically the way you would describe an MRI. An MRI is exactly that. It's a hydrogen imager. So basically we're looking at hydrogen nuclei, which is a proton. And so a lot of times as well, people actually talk about proton spectroscopy, which is NMR. An MRI is just basically a simple hydrogen imager. Yeah.
So I think anyone who's had an MRI knows that there's a magnet involved and it's generally a non-trivial magnet. Some people have probably heard of some of these real horror stories where accidentally in the hospital, a patient's wheeled in and there's a loose oxygen tank under the gurney that's wheeling them in and it goes flying across the room and hits somebody and can kill someone. So how strong is the magnet and why does it need to be so strong? Right. So the magnets, they come in different flavors. So typically it's regarded as a Tesla magnet.
And so a Tesla is roughly 10,000 gauss. And so a gauss is effectively what the North Pole can produce.
And it's actually the typical measurement for most magnets. But when we actually get into the MRI field, it becomes so much stronger. And the reason we actually kind of need that high Tesla field strength is because we're actually taking hydrogen, which is typically not that magnetic compared to like a magnet that we think about like a bar magnet. And what we're trying to do is we're actually trying to orient that little dipole of the water molecule or fat molecule a certain direction.
And that's what the static field does. And that's why it has to be so strong. So they come in flavors, 1.5 Tesla, 3 Tesla, which is double the strength, 7 Tesla,
And so the higher the Tesla they go, the more it's actually able to pull all of the hydrogens and orient them in one direction. Because as we're sitting here or anywhere, normally our hydrogen molecules are on water. We're just kind of bouncing around randomly, kind of pointing at any which direction. And then there is no kind of magnetic component to us. The hydrogens are spinning around just based on Brownian motion. And so when you actually go into a magnet, that strong magnetic field, these hydrogens basically kind of
turn and orient themselves in that direction. And so that's what actually provides the initial basis for an MRI. And that's why, contrary to what we see on TV, that magnet is always on. You can never turn it off because that magnetic field always has to be there in order to provide that orientation. And as well, the way it works is you actually have a superconducting wire that's actually running just above absolute zero degrees Kelvin. So it's roughly two Kelvin. And
And so you can't turn that off. This is superconducting wire. It has like pumps that are pumping all the time to keep it that cold so that when you actually put an electric field in like a loop of wire, that electric field is what actually generates the magnetic field in a perpendicular direction. So you have a generator that backs up if you lose power, which invariably you're going to lose at some point. Exactly. You have to have that backup power to always keep this pump moving this liquid helium so
that's surrounding the wires to always keep that liquid helium floating around, circulating around that wire to keep that wire near absolute zero Kelvin. Now, if we were to walk in the scanner today and everyone can sort of picture this, there's a bed running through a donut. What is the direction right now that that magnet is being oriented? The donut. So that's where that loop of superconducting wire is sitting in. And so depending on how it's put in, most of the time, the North will actually face away from the control center.
And that's the direction of north. Got it. And if I recall, there's like a right-hand rule on this, isn't there? There is. Very nice. So it can tell you which way the power in the coil is going. And it's actually going...
I guess if you're looking from the foot of the bed, it's actually going in a clockwise circle. And that's the right hand rule. The right hand rule. It's pointing in the axis. Okay. Now, aside from the fact, let's pretend we weren't wearing anything metal. If you walked into a room where there was a 10 or a 20 Tesla magnet, would you feel anything? And would it do anything to you that is harmful? The actual magnetic field won't do that much. Now, when you get very, very strong to a moving magnetic field,
you can actually start to feel it because it can actually trigger your nerve impulses to start moving. So sometimes people actually, if the magnetic field is too strong, they'll actually get twitching. And sometimes people who are actually around magnets all the time, they actually become more and more attuned to this type of a thing. And so if you have MRI technologists or people who are working with the high fields all the time, they can say, you know, when I go to the head of the magnet or like the north side of
I actually kind of feel something pulling. And sometimes people describe getting temporary headaches. And as soon as they step away from the field, it all goes away. Usually when patients ask me if there are any side effects or harm of an MRI, I mean, our lib answer is to say no, no, no, no, no, especially with a non-contrast. Like if there's, I mean, not that the risk of gadolinium is high, but
If you're just having a dry MRI, you say nothing, nothing, nothing. But I actually had a patient who had very, very, very severe migraine headaches and she actually had a migraine triggered by an MRI. And I truly believe that wasn't just a coincidence. I mean, I think her headaches were so severe. So, so I now sort of always couch my response as there's virtually no short-term or long-term consequence that can come from an MRI. But at least in the case of that person, you could trigger a headache. Yeah.
You can, because what it does is it can actually stimulate the nervous response. And depending on how strong the field is,
So for example, if you were to do a seven Tesla magnet, you're definitely going to notice it. And as a result, they'll tell people, look, you can't be in this too long because of the fact that you're actually going to stimulate. So I remember going back to learning about this. One of the other things that sort of strikes anybody who's had an MRI is they take a long time. So why is it that if you wanted to get an MRI, let's nevermind whole body, which we'll come to, but you just wanted to get an MRI of the abdomen that could easily take 40 minutes.
Whereas a CT scan of the abdomen can take two minutes. Yeah, and it's basically the way the images are acquired. They're a completely different mechanism. So if we go back and talk about the x-ray, it's basically like a single flash where you're actually looking through everything. The CT is basically this x-ray that's constantly on, spinning around, and basically sort of circulating around you. Whereas MRI behaves completely differently. And during the period of time of that acquisition...
What it's doing is everything that's inside the center of that donut is being pulled in a certain direction, all the hydrogens on your water and fat. And then the loud part of the MRI is actually a temporary magnetic field, which is countering that static field. And so it's actually now pulling all the hydrogens in the opposite direction.
and then in that opposite direction it actually turns off, and then the hydrogens reorient to where they were in that static field, and as they reorient they actually give off a different frequency. And that different frequency takes a while to gather,
And that's what we call the TR or repetition time or the TE of the echo time. And that you can't speed up. So let's talk about TR and TE because it's the TR and the TE that determine what sequence you are looking at. So again, I think the average person probably won't recognize these terms, but certainly anyone in the medical profession will.
we'll know the difference between a T1 weighted versus a T2 weighted image versus a spin versus an echo versus all of these things. So let's just talk about the difference between TR, that repetition pulse time, and then TE. Is TE the time it takes to relax back to its original position? So just discussing TR and TE, how do they differ in acquiring a T1 weighted image
which is the one that's really anatomically beautiful. It's the closest thing you see to, wow, I know what I'm looking at and I'm not a radiologist versus the T2 weighted image, which seems to highlight water more. So things that are water look more white, but it doesn't have the anatomic resolution. How would you differentiate those? Right. So the simplest thing to do, and it's actually quite fascinating, is I went through residency. People are always sort of stunned with, is this a T1 image or a T2 image?
and went through all that and was kind of like sort of a bit obscure and then when I started to do MRI much more it's like it became actually pretty simple. On the T1 image we actually see nothing but fat so fat gives a lot of signal which is what makes it nice and bright so we see a single element or I guess a single element that the hydrogen would be bonded to that we're looking at whereas a T2 we're actually now seeing two elements we're seeing fat and water and
And so those two elements are actually coming off at different frequencies from the MRI machine. And you have to wait a longer echo time to be able to pick up the water because it
returns back to normal much more slowly than the fat does. So that's our TE time. So T2 weighted images take longer to acquire because the TE is long because you have to wait to get both fat and water. What's the difference in the TR between the T1 and T2? It's all going to be entirely dependent on the machine. So you actually have to customize those parameters for every single machine. And so that actually kind of takes a while to actually kind of go and calibrate and kind of get used to what your eye is used to seeing.
And it's also going to be dependent on the signal, the overall magnetic field as well as overall signal to noise for that coil set that you're using. So each one has to be effectively tuned. And then what does it mean when you have these other things that come out? And God, it's been so long since I've done it that I don't even remember when we would look at spin, spin echo, spin.
all of these, I vaguely remember all of these other sequences we would order. I don't actually recall what they were. Give us a brief rundown of that. One of the things that MRI actually loves is just the different acronyms for everything. You gotta have it. It's almost like a, whoever can come up with the coolest acronym wins like lava and all these other things.
But effectively, there's three main categories of MRI sequencing. One is what we'll call conventional. So conventional spin echo. And so that's basically just waiting as long as you can for the hydrogen to completely relax and give off both its water and fat signal. And then we have what's called gradient imaging. And so that's actually, you're not waiting for it to completely return back to normal, but somewhere in the middle, you're actually kind of repulsing again. So you're basically hearing that noise of the machine turning back on and saying, you know,
We're not going to wait till they completely relax. We're going to fire up again. And just give us a sense of the actual time. How many milliseconds, if you're trying to get a T2 signal and you're waiting for that full relaxation, how many milliseconds is that directionally? It's actually going to be, it can be up as high as like 60 milliseconds or even longer for some of them. Okay. And when you do these gradient based tests where you're going to repulse, how quickly are you repulsing? You can actually repulse in like two milliseconds or even faster.
And then there's actually the third category, which is actually called EPI or Ecoplanar Imaging. And this is actually amazing. So this part actually allows you not just to be looking at a single slice of a person, but you're actually going and you're actually now running multiple slices simultaneously where you're actually putting two different fields on the person at the same time. And so as a result,
And it kind of gets complicated because we use the word gradient all the time. And so what a gradient basically means, it's effectively like a ramp from 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 start the image from your top down. First, we're going to put a gradient on from top to bottom. So it's going to be a little bit of a higher frequency at the top, a little bit of a lower frequency lower down. And then we're actually also going to look at phase from right to left.
And depending on how your body's oriented and where the blood flow is going to be, we're going to look at phase and frequency, which now bring us into the realm of a Fourier transform. So these are now with the pulses, we're effectively looking at all these repetitive sine waves. And we're actually plotting that in frequency and phase domain.
Right. And for the listener, we always talk that Laplace was only half the man Fourier was. That's like the nerdiest math joke I'm going to tell today. All kidding aside, how does one get into MRI radiology without a background in mathematics and physics? It seems it would be impossible. It's a struggle. I can actually remember with the group of residents that I was with training and great people.
that we actually had a physicist come in and was talking about MRI physics for a couple of days and trying to teach us all. And I thought, boy, this guy's really watering it down. I can barely hang on to what this guy is saying. Then I kind of looked and talked to all my colleagues and they were just bewildered. They had no idea what he was talking about. Because as far as an engineer is concerned, it's like Fourier domain, it's kind of like, that's sort of like the alphabet. Yeah, that's our bread and butter back in the day. Yeah. The difference with the MRI is that you start in this Fourier domain and
Because we're a three-dimensional object, when you're looking at a two-dimensional plane, that's the Fourier transform. When you now have that third dimension, it becomes what we call K-space. So it's effectively a two-dimensional Fourier transform, which is what the MRI world operates on. It's called K-space. So what we're going to do in the show notes here is we're going to link to some very common types of MRIs that people have, right? The most common ones that people have is...
You've tweaked your knee. You're going to get the knee MRI. You've hurt your back. You're going to get the MRI of your back. You're having headaches. They're going to do the MRI of the head, those sorts of things. So when you think about the bread and butter clinical practice of medicine, what types of MRIs, describe what those three would be. What sequences would be run to? If you wanted to evaluate someone's ACL, the ligament in the knee, what would you do?
What are you going to look at? The first thing you're going to do, and this sort of relates back to the plane X-ray, you're always going to look at things in two dimensions. So you're going to look at two planes in this case. And so you'll be slicing from right to left, top to bottom, side to side. And the beauty of the MRI is that based on how you orient your gradients, you can easily slice those three directions or actually in any direction you want, which is why we call it multi-planar.
And so if we were to look at a simple thing, like a simple image, like a knee, so we always like our anatomy image. So that's our plain T1 because fat is beautiful and it actually allows us to see everything really well. And it looks like what we're actually accustomed to seeing, um,
And so we do a T1 sequence, then we'd also look at a T2 sequence or a T2 fat sat sequence. And what that actually allows us to do is on a T2 fat sat, we actually go- That's fat saturation. Yeah. So T2 fat saturation, what we're doing is we're taking T2. So now T2 looks at two things, so fat and water.
And then we actually suppress the fat. So really all we're seeing is water. And why that's most interesting is because edema. So when there's something going wrong in the body almost anywhere, edema happens. It's like if you bang your hand and it swells up, that swelling is edema. You injure your knee, it swells up, that's edema. And so if you actually bang the bones on your knee, so you've actually injured the cartilage, you're going to get edema happening in the ends of the bone as well as in the cartilage.
So that's why the T2 with fat saturation or removing the fat signal becomes so powerful because it effectively now turns into a edema imager. And when we know when there's edema, there's a problem. And that's kind of a simple concept in MRI that is quite often lost, but it's very, very important. And then when you look at somebody's brain, for example, we just reviewed my MRI recently. So one thing that stands out, I think, is
the exquisite anatomic detail you're getting that seems to look far better than it does in CT scan. And secondly, it's the fact that without any contrast, you're able to see
as though you did an angiogram on all the vessels in my brain. Now, is that something that any MRI can do, or is that just something that the MRI here can do? Most MRIs should be able to do that. And so when we can sort of think back to what an MRI is, so again, hydrogen imager, but it's also a big, powerful magnet. And so what makes our blood red is actually the iron that's contained within it.
So what you can actually do is you can take all the blood that's, let's say, flowing to a particular organ like the head. So anything that's flowing up and you say, okay, I'm going to actually excite anything going up north to the brain. And so therefore that's arteries. And so then you'll actually get to see all the exquisite arteries in your brain just by exciting that blood. I had never realized something so obvious as you just said it, but
That's one part of the body where it's really easy. I mean, the limbs would be the same where directionally it's so clear, you know, which way your magnet is oriented, you know, which way is blood flow away from the heart.
And you've got this beautiful iron floating around in water. Right. That's one of the beauties of MRI. It's that there's all these different things that you can actually add to it. And so not only that, you can actually excite anything flowing in one direction, but you can actually also pick off the frequency that's different between oxygenated arterial blood and deoxygenated venous blood. And so that comes into a different sequence called SWI or susceptibility weighted imaging.
where you can actually look at the deoxygenation status of venous blood and you can get spectacular contrast of the small blood vessels in the brain using that sequence. I remember the first time you did an MRI of my head. I don't know why I was more nervous about seeing that than anything else because
We sort of remember the most extreme, horrible stories, but I mean, I know people who have died of aneurysms. You and I were even speaking about a patient a few hours ago about this. I used to ride a bike with a guy who was maybe six years, seven years older than me and was at Disneyland one day with his kids and had a horrible headache and dropped dead. And he had an aneurysm, which is congenital. And so, yeah, I was sort of like really nervous, even though I realized
straight probability basis, the odds were quite low. They weren't zero. And I figured, well, it's better to find this now because you can treat these things electively quite easily. But once they rupture, the mortality is incredibly high. The mortality of a ruptured aneurysm is over 93 to 95%. So most people don't make it. Whereas when you do find them earlier, there's all sorts of options such as coiling where you can actually treat it or clipping.
And so that's actually one of the real powers of being able to kind of see what's going on without any injection or anything like that. You can see the exquisite detail of the arteries. And if there is a problem and we've found a fair number of people with them, you can actually save their lives. What is the frequency? Admittedly, you have a, you could argue a somewhat biased population because they're more health conscious. Obviously, anyone who can afford it.
to just pay for an MRI out of pocket is going to have a socioeconomic advantage. But if you argue that that's still a reasonable cross-section of the population from a genetic standpoint, which is what we're basically asking,
What is the prevalence you find of aneurysm in the brain? So when we actually scanned a thousand people, we actually found eight intracranial brain aneurysms. So 0.8%. That's higher than I would have guessed. Does the literature support that? The literature is actually a little bit less. And the question is, is that because you don't find them? Because basically people have passed away and we don't know what happens to the elderly because...
If they pass away, it's natural causes. Yeah, we're not doing the autopsies. Now, there are other aneurysms that are not quite as lethal but are really bad. And the two that I remember from residency were splenic artery aneurysms and popliteal artery aneurysms. Do you see those? And if so, at what frequency? We found only, I think, two splenic artery aneurysms, but they are particularly deadly.
And now the popliteal arteries, haven't seen many of those. No, I haven't seen those. And then those should be actually easier. You can palpate those on a thin enough individual. I was going to say, those are actually easier to feel and to see and to look at, but we actually haven't found any of those. I'm kind of still shocked. That's a frightening statistic, Raj, to think that almost 1% of the population has an aneurysm in their brain. And one of the things that we actually find though, and this may be showing the genetic component to it,
is that when you find it in one person in the family, next thing you know, all their extended family's coming in, right? They want to know what's going on. We looked into this three years ago. I have a patient, a young woman, probably in her late thirties. Her mother died very young when she was very young. The patient was very young and the mother herself was quite young from an aneurysm. It was not in the brain, but I'll, for the sake of trying to protect her confidentiality, I'll
refrain from saying what part of the body it was. And then when we dug into her family history further, we found another person who had died of an aneurysm in yet a different part of the body. So not aortic where you normally see that link to atherosclerosis, but a different major vessel. And our team did a bit of work on this and actually found evidence that there really was potentially a genetic component here.
And so we petitioned her insurance company to pay for an MRA, a magnetic resonance angiography, which is basically what we're talking about here. And they declined it, which really irked me. And we fought with her insurance company for six months to get this paid and they denied it and they denied it and they denied it. And finally the woman just paid out of pocket for it.
And I was blown away at how much it costs. Do you want to take a guess at how much it costs to get an MRA in the United States? I've seen some interesting pricing. It was $9,000. Wow. Wow. That's a, that's unbelievable. Yeah. And it was negative. So we were happy and she was obviously fortunate enough to be able to afford that. But it upset me that we couldn't make a case to the insurance company that
Two people, one first degree, one second degree related to this woman have died from an aneurysm young. Yeah.
And they were like, yeah, that's cool. Wow. That's a tragedy. So let's come back to now what you do here, Raj, because I've been around a lot of MRI. And if we bring this story back full circle four years ago or whenever we were introduced, the question that was asked of me was, hey, is this thing kind of cool or what? And I came up here and I spent the full day with you and I thought, yeah, boy, this is really cool. But so many things that you were doing just seemed counter to what
what we were seeing in the big shot hospitals. And for starters, you were using a puny magnet, right? So one of the things hospitals love to brag about is the size of their magnet, right? I'm going to just try not to name any hospitals and offend everybody, but pick your favorite institution. We've got the newest four Tesla magnet. That probably was in the top five questions I asked you. Oh, so what size magnet are you using? And you said, we're using a 1.5 Tesla magnet.
And I said, oh, that's interesting. That seems a little bit JV. So explain why you use a magnet that is not at the peak of what you're capable of just from a technology standpoint. Well, it really sort of depends on like basically how you tune a magnet. So I actually kind of view a magnet as very much like a smartphone. If you actually build the right hardware, you can actually really get it to sing and do an amazing job.
And so with a 3T magnet, one of the things is you can get some pretty exquisite imaging as we see quite commonly. And really, there's a lot of bragging rights associated with it. We're not much of braggers up here. We just actually want to do the best imaging we can and actually tune the machine as optimally as possible. So with a 3T magnet, one of the things that actually commonly happens is that when you look at the wavelength of a 3T, because remember, it's electromagnetic fields actually go hand in hand, and those are actually wavelengths.
And so the 3 Tesla wavelength is roughly 15 centimeters, so it's the width of your head. 1.5 is roughly 30 centimeters, so it's the width of most people's shoulders. So as a result, you actually start to get a lot more penetration with a lower field magnet.
And so that way you're actually able to see things quite well when you're particularly having everything tuned to that particular wavelength. And quite commonly, when people are purchasing machines, they just don't know the physics of how the static magnetic field, the gradient magnetic fields, the coils, and there's roughly about 150 parameters per T1, T2 fat saturation sequence that you can actually adjust to make it work the way you need it. And most of the time,
What commonly happens almost everywhere is that you'll have the vendor will actually come in and set the standard parameters. And from there on, it's kind of like, let's make it as simple as possible, push a button. And that's kind of not what I do. We don't want to just push buttons. We actually want to understand how it all works, how it can be optimized to the person that's coming in and how the entire system from front to back is optimized. So we're maximizing our signal to noise.
And when you maximize your signal-to-noise, that's when you actually really get a lot of speed and detail. And that's where one of the real values of being able to talk engineering or physics with an MRI physicist and also then put on your clinical hat and kind of saying, well, this is what I want to see. This is the level of detail I need and the level of resolution that you can really tune the machine to.
where you want it to be. To me, of course, that was the analogy you came up with. The first one that jumps to my mind is looking at sort of the heyday of F1 in the late 80s and early 90s when the cars had become monsters. So if you look at the McLaren MP44, which is regarded as either the greatest or second greatest Formula One car in history, the only other car that could probably rival it would be the 1993 Williams.
It had a 1.5 liter engine. So for any gearhead listening, that's a really tiny engine. Like your Prius probably has a bigger engine than a 1.5 liter engine. And yet it produced 1200 horsepower redlining at something like 15,000 RPM.
And I just remember being a boy being so obsessed with that. Like how could that possibly happen? And I remember looking at my dad's station wagon, which had like a five liter Chevy block in it and thinking, how is this thing so inferior? But wow,
In the end, like you can engineer, I mean, I think the technical term is you can engineer the shit out of anything, right? That would be. Exactly. And that's exactly what it is. And it's very analogous to the formula one. And a lot of people kind of, they're more into the bragging rights of like the bigger, the bigger, the bigger. It's not always bigger. It's kind of like, if you really understand what you're doing and want to get underneath the hood, you're going to get under the hood.
You can take that 1.5 liter engine, you can put the turbochargers on it, you can put, you know, like the multiple valves and everything to actually get the torque and horsepower you want out of it. But most people don't think that way. They think bigger is better. How did you...
do all this tinkering because you basically have here in Vancouver, a piece of hardware that doesn't exist anywhere else in the world. And you've layered on top of that software that is now also in a league of its own. And that's even more complicated. I just am interested in this hardware. I mean, one of the things that I send a number of patients here and
Usually the first question I ask is, why are you sending me to Vancouver? I live in, fill in the blank, some city in the United States. We do everything the best. There's no way, Peter, you're telling me there's an MRI in Vancouver. In fact, I told my parents the other day, I was coming to Vancouver to get the MRI. You could almost hear them look at me through the phone like, why are you coming to Canada? Yeah.
So, I mean, not to toot your horn too much, but you're doing something very different, Raj. So how did you...
go through this process of tinkering with the 150 variables at your disposal to come up with this super custom pimped out hardware that doesn't resemble anything else on the planet. So part of it is it's like the, the biggest problem with me is that I'm an engineer in medicine. And so when I kind of go through, it's like, I say, well, what do I want to know? What do I want to see and how do I make it work? And so I kind of started sort of the backend and say, okay,
What I want to know is exactly what's going on everywhere in the body and what are the different sequences that are going to get me there. And then I kind of work backwards. And then this is where you put your engineering or physics hat on. And you actually wind up starting to talk to like the MRI physicists who are, there's a plethora of them. They're almost everywhere. And they love to talk to doctors, but just most of the time,
doctors can't talk to them or vice versa. And that's when you start to really kind of get under the hood and really kind of understand how to make this work. And then you travel around to different academic centers or different places. And you wind up spending time with the people who actually really understand the hardware. And those are mainly the physicists, very similar to a mechanic. It's like, if you want to figure out how to make your five liter machine,
behave like a thousand horsepower, you talk to the mechanics who know how to do it. Don't try it yourself, right? They've already been there. They've seen it. They've worked on things forever. And that's actually how a lot of it happens. And so
We would actually be having some of the top MRI physicists sort of saying, hey, Raj, can you test this? We wrote this sequence. And a sequence is basically like a filter, like a T1 or a T2 or a fat saturation. 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 subject, because I also know what I'm looking for. And then we'd have a feedback loop, one or two of my MRI technologists here who would actually sort of push the buttons and run the machine. And we'd see what it would give me.
And I knew from all the other imaging training that I would have what I would be looking for. So I put my nuclear medicine hat on and say, okay, from a functional point of view, this is what I want to see. Then I put my radiology hat and say, this is what I want to see from an imaging perspective. And let's define that a little bit. I mean, objective is important. So when you went about this process, what were you optimizing for? Were you interested in...
primarily in detection of cancer or what was the problem you wanted to solve clinically? The first thing I wanted to do is, so when we talk about the nuclear medicine, so when we're injecting somebody with radioactivity, we want to basically optimize that dose that we're giving to somebody. So that means we want to cover everything from head to foot. We don't want to just look at an individual body part and we want to see how it all works. Then when we go to radiology, typically we're just doing a snapshot of an individual part like a head or a neck or a torso and
And so I kind of thought, well, if all these MRI machines that are out there, all they're doing is looking at individual body parts. And I thought, if I customize this hardware with a few things that might allow me to move people around while they're on the table, while they're laying there, will I maybe be able to connect the head with the neck, with the chest, with the abdomen? And so I actually, when I bought the hardware myself, I kind of put together probably about 50 options.
that the vendors kind of said, you're crazy. We've never seen any of this stuff. Just with the thought that, you know, I think this might work. This is where I was kind of looking at all the different options and kind of knew what they could possibly do. And I thought, if I build this hardware this way, will it work? And it was a complete guess, but an educated guess.
And then once I put that hard work together, then we started to test and test and did more and more. Then we would start talking to more physicists. The vendors themselves actually have a lot of good resources with very technologically capable people. And when I started to put this together, then I kind of thought, okay, what would I want? If I'm a patient, what would I want to know? Well, number one, I'd want to know that my brain's okay. I'd want to know that the arteries in my brain are okay. They're not going to rupture.
And then I basically want to say, whenever I go into any test or anybody goes into the doctor and gets any kind of imaging test of any kind, the first question out of their mind is, do I have cancer? Yes or no. And in nuclear medicine, most of the tests are binary. We can actually answer that with a yes or no. In radiology, it's not so clear. It's kind of like, maybe. And you're actually kind of playing more statistics, like probably not. And I thought, how do I marry these two together? And this is where an MRI becomes a beautiful machine. And the fact that it actually allows you to take that
yes or no binary answer of functional nuclear medicine and combine it with the anatomic localization and understanding of tissue types that radiology has. And so I merged those two together on the one machine. And what is the functional arm that you've brought into it? Yeah, so the functional arm is actually an area that's actually growing a lot in academia. It's actually called DWI or DWIBS, which stands for diffusion weighted imaging with background subtraction. And so what we're doing with DWIBS is
is that we're actually looking at water at two points in time. And so we're actually looking at it within about 60 microseconds of water motion. And so by doing that, what happens is that you first look at water at one point in time, and then you look at it at the second point in time. And if it hasn't moved, it's because it's not allowed to move. It's effectively trapped between walls. And so that could be because of the fact there's a tight cell membrane, or it could be because components of a cell move
preventing that water from moving. What's the time gap between those two samples? Six microseconds. Wow. And so when you see that something isn't moving, when you see that water is being forced to be stationary as opposed to moving according to the stochastic prediction you have, what do you infer clinically about that tissue? So as soon as you start to see that water is being prevented from moving, that means that there's basically going to be a high density of cells there. So a big cluster of cells.
And so it's very much like, I actually call it the lump detector. So it's basically like they tell women for breast cancer, feel for a lump. And basically when you're feeling for a lump, that's hard spot. And so the reason it's hard is because you have this increased cellular density and
And so with that increased cellular density, that's where water is restricted from moving. And that's what DWI or diffusion weighted imaging does. And why it's called DWI is because the fixed lot of diffusion basically means that the normal diffusion of water allowing it to move a lot is being completely restricted and it just doesn't have the ability to move. You know, I usually tell patients about this part of the MRI process.
telling them something that I think many people outside of medicine would find surprising. When you do what's called a laparotomy, when you open up a person's abdomen and let's say they have colon cancer. So the colonoscopy has confirmed that, of course, you have a biopsy. So now you're going in to do an operation to remove their colon, but you still have another step along the way, which is you have to complete what's called staging. You have to ask the question, has this cancer spread?
So usually the first thing you're doing is you're running your hand along parts of the abdomen you can't even visualize, the entire surface of the liver, even behind the liver, something you won't see. It's actually unmistakable what cancer feels like because it is so in contrast to what normal tissue feels like.
And even the colon, before you cut it out, if you just reach in and pick up a piece of the ascending colon, it's not remotely subtle where the cancer is. It's entirely obvious just based on the firmness of the tissue. And even when I talk to surgeons who operate on parts of the body that I didn't operate on, such as the prostate or things like that, it's the same thing. And the example you give with breast is perfect. And so it really is this amazing ability to pair
exquisite anatomic detail at resolutions that we'll discuss, but basically now approaching one by one by one millimeter resolution anatomically,
with now this functional property of firmness. Is that an accurate statement? It definitely is. So we're actually combining the anatomic and functional, and that's where just like on PET-CT where that famous one plus one equals three is exactly what we're doing. And the beauty of it is there's absolutely no radiation, so there's no risk. So the risk, it seems, because one of the things I do explain to patients is who should consider doing this, right? And my view with cancer screening is disincentives
It's just a very personalized decision. I don't think it is for everybody to do the kind of stuff that I do or that a number of my patients who you've now scanned have done over the past three or four years. And when people say, is there a harm of doing this outside of the probably rare, rare event of getting a migraine headache triggered by the magnet? I say there is a harm, the harm of a false positive.
The harm is that we see something that turns out in the long run to not be cancer, but in the process of going down the advanced diagnostic pathway to get there, you are either physically harmed by something we do subsequently, for example, another biopsy or a biopsy or a subsequent biopsy,
And of course, the emotional toll it takes on you to see a shadow in this part of your body and have to sit there and have a discussion about what it could be, what it's probably a cyst, but it might be a tumor. We probably need to do follow. I mean, to me, this gets back to where we were a while ago on the discussion of sensitivity and specificity, right? So if somebody came along and said, I have a test that is 100% sensitive, but only 50% specific.
I'd throw it in the wastebasket. I mean, it would serve virtually no purpose for reasons I could walk the listener through in terms of positive and predictive value, negative predictive value. So when you think about the sensitivity and specificity of the technology that you've developed here, which again, we haven't even really done justice to getting into, we've talked a little bit about the hardware. We haven't even got to the software. I'd love to talk about that a little bit. Do you think about sensitivity and specificity by tissue type or
by cancer type? How do you in your mind wrap your head around that? So typically the way I kind of look at it is really almost organ by organ. When we're actually kind of going through, for example, in the liver,
basically the simple thing we want to kind of know, is there a problem? Yes or no. Like really, that's the simplicity that the average person and I put myself in that category wants to know, do I have a problem to worry about? And that's where I kind of say by combining this functional as well as an anatomic imaging together, we're actually really able to nail that down. So
In our 1,000 people that we did, the fascinating thing about this is all these people, we actually followed them up and actually talked to them and kind of found out what happened. And so we actually had two false positives. So these were two people where we kind of thought, okay, there's a problem here that you need to get addressed further by their further imaging techniques.
and see what's going on. And of those two false positives, one was a male with asymmetric breast tissue. So he actually just had one sided breast tissue. We didn't know what it was. It's like, so meaning you, he came out of the MRI and you believed he had breast cancer, which most listeners might think is odd, but it turns out men can get breast cancer. It's just virtually an exceedingly rare. Exactly. But that's basically the DWI showed a difference in density between one breast and the other. Yeah. And so we're like, why is that?
Most of the time when men actually have gynecomastia or they have breast tissue, it's usually bilateral because it's hormonal. But to have unilateral is somewhat odd. And so as a result, we sent this person to an ultrasound, which is commonly done, and
And they too had no idea. And so they actually also made the call to biopsy and it came back as normal breast glandular tissue in a male. So let's talk just about the harm there. So emotionally, that man probably spent a series of, well, if it was in Canada, a year. If it was in the United States, a week. Being stressed out about this, or I just can't help but take digs at your healthcare system as you take digs at ours. No, I'm totally teasing.
So there's a legitimate emotional strain here, which I don't think anybody who's known someone who's gone through that or who's gone through that themselves, you just can't deny this. And I've not lived it personally, but I've seen it and it's very difficult. And then secondly, he had to get a procedure. He had to get a needle stuck into his breast tissue. And look, that's on the scale of procedures, that's still pretty minor, but-
It's not trivial. So what was the second case? And so the second case was actually a woman who basically had a seatbelt injury to her breast and actually wound up having unusual scar that had actually trapped fluid in it. And so this person actually should have, but never did actually have any mammograms because that would have led to the same conclusion that we don't know what this is. So that was the second case where it's kind of like, there's something unusual going on in this breast. We don't know what it is.
but we didn't actually have any proper history from her. And so we- How old was she? She would have been late 50s. A woman in her late 50s had never had a mammogram? Surprise. It's out there. Even in Canada? Even in Canada. Yeah. That in and of itself is very hard to believe in a country where- It's free. Yeah. Yeah. And then what would bring that patient in to get a whole body MRI? The person actually kind of felt that I just want to know where I'm at.
And it's like, I don't believe in the radiation from mammography. And I keep trying to tell them, look, it's so minimal that the benefit outweighs the risks. But they're like, I want the MRI instead because number one, patients kind of know that it's the most detailed exam you can get. And as well, there's no radiation. So we actually had the patient and it's kind of like, yes, there's this, I don't really know what this is going on here. So we sent them off to a facility that does nothing but women's imaging and
And they too didn't know what it was. And so they stuck a needle in it and it actually came back as a trap. Something fibrous. Exactly. It was actually trapped scar tissue. And at that point when we'd spoken to a woman afterwards, we're like,
Did you ever have trauma? Like, why would you have scar to that area? And it's like, oh yeah, I was in a bad car accident. And that was it. It was a seatbelt scar. Those are two pretty interesting false negatives, right? Both breast men, women, I would have always maybe guessed or been most concerned about the false positives that occur deeper in the body. I always tell patients the call I'm always most afraid of getting is,
the little shadow in the pancreas where you just don't know, is this an adenocarcinoma of the pancreas, which of course is something that if you're lucky, you can resect it. And if you're even luckier, you can survive it. And I guess that's the only shot you're going to have at surviving pancreatic cancer is an incidental finding. Really don't think anybody that presents with pancreatic cancer is going to survive it, at least not as an adenocarcinoma.
But then you worry about, well, what if it's something that turns out not to be cancer? And you hear these horror stories. There's a very famous one, I believe at Stanford several years ago, where a woman went to a sort of drive-by CT clinic, got a CT scan, showed something in the pancreas. She ended up going to get a biopsy and I believe it was an ERCP. I did biopsy.
One complication led to another, led to another. She died of sepsis. And by the way, it turned out she didn't have pancreatic cancer. I don't know that firsthand, so that might be a bit of a wives' tale stretch, but certainly that's a very popular story in the Bay Area. But it's the cautionary tale, right? Definitely it is. And that's kind of where the real value of actually having MRI as opposed to CT comes in, in the fact that when we're looking at organs, particularly like the pancreas or any of the visceral solid organs,
We're looking at about seven different filters, looking at it different ways, top to bottom, front to back, to really be able to see what's going on. And that's where what we call contrast density becomes really important in the fact that
When we're actually looking at the pancreas in particular, we can actually pick out the pancreatic duct as well as the bile duct and be able to see that just standing out against the rest of the organ. And one of the first most common things that pancreatic cancer likes to do is to actually start to block that duct. And so that's why when ERCPs are done, they're actually looking for cells of pancreatic cancer. And an ERCP is basically when they go down into the mouth and the esophagus and they actually go and take a trace of fluid from the pancreatic bile duct.
So one of the other things that kind of amazes me when we go through these images here is when we've talked a little bit about the hardware, though, actually, I kind of want to come back and ask more hardware questions, but it's almost like you've created your own software now as well. I had never seen this. Is it commercially available to have that rotating diffusion weighted image map? Is that a commercially available piece of software?
Or did you guys make that? We actually built that as a display tool. And that's actually effectively taking a page out of the Nuclear Medicine Positron Emission Tomography or PET-CT Handbook.
And the reason why we actually put it together is because it actually allows you an effectively a pretty efficient viewing to be able to see what's going on through the entire body. It's almost like making a transparent person and where basically any of the black spots that stand out would be the hard spots or the firm areas. And the one that we've just looked at earlier, I remember you saying that
If I understood you correctly, one of the advantages of using a quote unquote low power magnet like you're using is you don't have any of the gaps in the spine. You've got this, everything that you showed on that rotating diffusion weighted image, you had the dark brain, obviously full of firm fluid. And then you have this dark, beautiful tail coming out of it, which is the spinal fluid, but it was perfectly smooth. Right. And that's actually one of the important things because magnets actually have a lot of homogeneity problems. We call them.
and the fact that you want it to be perfect so that the field in between the top and the bottom and the left and the right are identical. And as soon as you put a person in there that comes in various sizes and shapes, they actually distort that magnetic field.
And the sweet spot for the magnetic field is perfectly in the center. And so when we put all these protocols and built all these things, we actually built it for different body shapes and we can actually go and tune it for all these body shapes so that the goal is that no matter what, when we're doing these rotating images, that it looks like a normal person, not a segmented piece of a person. Yeah. It's funny you say that you took a playbook out of the PET CT. That's exactly what it looks like. It looks just like you're looking at the FDG PET,
juxtaposed with the CT. Right, and that's the entire purpose. And so that's where I talk about the MRI being this tool that can actually combine functional imaging of, in this case, DWIBs or DWI, diffusion-weighted imaging, and the MRI being the equivalent to the CT, which is far more tissue weightings in detail. It's where the 1 plus 1 equals 3. Now, if the radiation didn't bother you of a whole-body PET-CT, and of course it should bother you because a whole-body PET-CT would be
more than 50% of your, it'd be probably close to 80% of your annual allotment of radiation, right? If not more. It'd be quite high. Yeah. And depending on if you live at altitude or where you live, right? So if you're at sea level, you'd probably be allowed one a year maximum, if not one every two years. Yeah. So putting aside that issue, which is not trivial,
What advantage do you think that the MRI with DWI has over the PET-CT? And where does the PET-CT have an advantage? So if you go either by histology, by tissue, by tumor type? With the PET-CT with radioactive glucose, one of the areas that actually doesn't work very well at all is the brain. And the MRI is always known as like the best image of the brain.
The PET-CT, you can actually miss things in the brain because what you're looking for with the radioactive glucose is areas of increased glucose utilization. And the brain in particular is a glucose, that's all it can use unless you're in ketosis. And then the other problem is that the glucose is then excreted by the kidneys. And so the kidneys now become difficult to see because they're actually full of glucose. And as is the bladder, you can't see a thing in the bladder because it's full of the accumulated glucose.
As well in the prostate, prostate is very, very poorly perfused, and as a result, it doesn't get a lot of glucose coming to it. And so PET is actually almost entirely useless with FDG at looking at the prostate. Diffusion-weighted image of the prostate...
coupled with the more advanced molecular tests, the 4K as an example of a blood test, in my mind have totally revolutionized the way we think about prostate cancer. So we now have a blood test that produces much better resolution than just a PSA. But more importantly, we have this MRI. And even in a practice as small as mine, I have had two patients for whom I
PSA is high. 4K comes back high. So these are patients who now have a 20% chance, maybe 16, 18, 20% chance of having cancer in their prostate or having metastatic cancer over the next two decades. That's basically what the high 4K tells you. In the olden days, we would have just biopsied them. And now we run them through
this MRI? And the answer is, nope, that's totally fine. Right. And then that's actually where MRI becomes very, very powerful, particularly with the DWI. And I think in many countries, it's now coming to us and becoming more popular, but in Australia, in Europe, particularly UK, Scandinavia, it's actually the de facto standard. Basically almost all men are actually getting screened with MRI. Wait, wait, wait. Did you say in Europe and Australia? Yeah. They're actually doing it with a DWI.
And so how is that even possible that countries with single payer socialized medicine could use an MRI for a screening tool? I mean, that would be unheard of in Canada, wouldn't it? Well, you know, we just don't have the access to the number of machines here. But I think one of the things that people are actually finding with screening for the prostate is that all men are either going to die with or from prostate cancer. And so you really want to be able to separate those out.
And up until MRI with DWI came into effect, there was no real way to do that. So you'd be doing PSA or 4K, and all that would do is say, yeah, there's an increased risk of something going on, but is it going on? So PSA in particular, it can actually be elevated for three reasons. One, prostate cancer. The other one, inflammation or prostatitis.
And then the third being enlarged prostate. And so if it was up for any of those causes, then you would actually go and take a biopsy, which actually comes with risks. But the whole idea is that all the staging was based on that tissue sample.
Whereas what's happening very similar to the breast is kind of like a lot of people are saying, well, treating this is like a big deal. I don't want the biopsy and people get a choice of what they want to do. And a lot of men are saying, look, I want to see what's going on. I want to see if there's going to be a change. And if it actually starts to grow or something's growing in the prostate at an accelerated rate, that's when I want to deal with it. Whereas if it's actually just there and holding still and not changing much, I'm
I'm not going to worry about it because something else may take me first. Is DWI going to have the same effect on breast cancer? In other words, if you could put resources aside for a moment, if a woman could have a mammogram and a DWI MRI, and it's important to point out that you can't eliminate mammography because we're going to come to this, but MRI has its own blind spots and small calcifications would be a blind spot. But with those two tests, mammogram and
And DWI, MRI done the way you guys are doing it, not just off the shelf. Are you going to miss breast cancer in those situations? Pretty unlikely. And actually there's been a couple of really nice big studies that have finally started to come out from groups at UCSF and as well at Sloan Kettering, Memorial Sloan Kettering in New York that have actually shown that. You did your fellowship at Memorial, didn't you? I was actually there for quite a while actually doing PET CT. Okay. Yeah, yeah. Amazing institution. Absolutely amazing.
But what's actually come out of the MRI group is that basically if you actually use DWI with MRI, you actually are as sensitive as giving a contrast injection breast MRI. Wow. But that's diffusion done right. And the problem is out of the box, it's not always done right. Yeah, that's the challenge I think for the patient, right? Is the patients, look, you kind of need a PhD in physics. Let's be honest to really understand that.
the nuances of MRI, I consider myself pretty technically smart when it comes to the physics of this stuff. And I would not feel competent to try to differentiate or even parse out the differences between scanners. In fact,
anytime I'm sending my patients to a scanner, I sort of have to rely on other people to help me. I have to reach out to experts and say, Hey, is my patient has to get this scan done in New York or in San Francisco or LA? Is this the best we got? If they're not going to get on a plane and go to someplace where I know exactly what they're going to get. So, um,
That's a significant challenge, right? Because there's people are going to listen to this and think, okay, well, as long as it's diffusion weighted imaging MRI, it's perfect. Yeah. And that's actually the biggest problem with MRI. Like earlier on, we talked about CT having units of Hounsfield, like Hounsfield units to actually sort of calibrate and standardize them. Unfortunately, MRI has no standardization whatsoever.
And there's actually a movement called Kiba, or Quantitative Imaging Biomarkers Alliance. It's a component of the Radiology Society of North America that's actually really trying to push to standardize the amount of signal-to-noise coming off of MRI machines with the goal that if you actually get a scan at one site or another site, the image quality is the same. Right now, it's really...
Not that at all. And it really is sort of caveat emptor lookout. So right now, if somebody goes to Shreveport and gets a 256 slice CT scanner on a Siemens, pick your favorite model, and they do the same thing in Seattle...
You can share those data across radiologists and it can be made to look identical. Your acquisition is the same. Relatively. So what I mean by that is that the actual amount of signal on your film or on your screen is
water is going to be zero. And so the Hounsfield unit is always going to be exactly calibrated. So what's the opposition? I mean, that seems like a no brainer. What is the opposition to doing this with MR? It actually relies on the vendors coming together. And a few years ago, we actually spoke with a bunch of the vendors and saying, you know, look, why don't you guys do this, particularly for a diffusion where it's actually so important because this is such a new and powerful sequence. And,
And they all kind of came back and said, well, you guys write a white paper and then we'll implement what you said. And this is fortunately starting to move forward with this organization, Kibbutt of RSNA. And they're doing it organ by organ. So there is a bit of a standardization for prostate, for liver, and as well, breast is now coming out. And that was actually, the breast was led by a group out of University of Washington. And the overall leader for this is a person named Michael Boss out of, now he's the American College of Radiology.
And this needs to move forward because otherwise people have no idea what they're getting. And it's really sad because even if you walk down the streets, for example, in a place like New York, I used to live literally 20 feet from a MRI shop.
And they had all these sort of images and what I consider just sort of bogus propaganda all over their window. Like, why go down to Memorial and get your MRI there when you can come here and do a standing MRI? It's comfortable, it's fast, and blah, blah, blah. And I'm thinking to myself, and it sucks. So, and again, I don't know that that exists in Canada, but certainly in the United States, there's a bit of a cottage industry around MRIs.
one-stop shop scanners that I think patients just don't know what they're getting into, right? Right. And I don't know how well it works in the United States, but it really is. It's like because of this lack of standardization in the field of MRI. And it's really unfortunate because this is, of all the imaging tools, it's the most powerful, but it really does need this ability for standardization. And it may also sort of be the fact that in order to make it standardized, you need to get the physicists together with the radiologists who are basically the eye of the final image to
And quite often that doesn't happen because of the language barrier. Right. And of course, it's not, it's the language of physics is the language. Going back to the hardware for a second, where do you see things evolving? In other words, if you had to project where you think you, with the right technology, would like to see this in five or 10 years, what could make this better? What I'd actually like to do, and when you see sort of what we're doing, the speed with which we do and that the detail and resolution that we're able to acquire in about 55 minutes is really unprecedented anywhere. But
But I know from a physics point of view that I could speed this up further. Right now, everything we're doing is perfectly within FDA specifications. There's nothing outside of the box, but I really would like to push this and go outside of the box. And what that really requires is a lot more computational horsepower. It's really difficult to do all that computation within a single CPU machine on site, whereas I expect that in the future, as long as computers get faster and faster, you can actually do a lot of this stuff computationally and make it much faster and
The goal would really be to actually have these scans that we're doing, you know, under half an hour, even faster. And it can be done from a physics point of view. It's not a technological barrier. Even with the magnet that you have, even at 1.5. Yeah. Now, I had my scan today. I
friend had a scan today. And one of the things that people always talk about when they're done these scans is, my God, it gets hot in there. What is it about a whole body MRI, even one that's done in as short a period of time as 55 minutes, that makes it so uncomfortable by the end in terms of body temperature? Really has to do with the amount of energy that's being absorbed. So what we're doing with the electromagnetic field is you're actually putting in radio frequency, right? And that radio frequency is always also coming out. And that radio frequency is the same thing as a cell phone would get.
That's called SAR or specific absorption ratio. And the hydrogen ions are basically moving around and that's basically effectively heating you up. So it's not quite like a microwave, but you can actually think about it as a microwave. The wavelength is exactly very similar to an AM radio. And so your cell phone is typically far more powerful. So as an example, I went and did the calculation a while ago on how much SAR we're actually putting into a whole body prenuvo scan. And
And it's equivalent to talking on a cell phone for about four hours. Interesting. But it concentrates it across your whole body. Right. Yeah. It's funny. Every time I get an MRI or a whole body,
the first 30 minutes, I'm like, yeah, it's not so bad. And then the last 10 minutes, I'm like, get me out of here. Right. And we've actually done it that way on purpose because we kind of know that the way we kind of run our sequences or filters together is that we actually kind of want to get as much information in such a way as possible. Yeah, you do the head first and that's not nearly as much as doing the abdomen and thighs or probably where a ton of that heat gets generated, right? And it's sort of knees to abdomen. Right. And so when you look at basically the overall blood flow, which is what cools your body,
Well, the brain takes 20% of your cardiac output. So it's basically like this big cool. It's this big heat sink, right? It just cools everything away. Whereas when you get down and lowered to the legs, which you're all muscle, you're
It's going to heat that up. And so that's why we figure out how to orient these and what organization to make, what plan of sequences to make it not as uncomfortable. Commercially, what's the best off-the-shelf scanner that could come close to producing the resolution you're producing? Is it fully isotropic? It's isotropic in the brain, but in the rest of the body, we're actually doing more conventional clinical images. Tell us what isotropic is. I'm sorry, I should have clarified that.
Sure. So what isotropic basically means is that we're basically slicing you in cubes. So a one by one by one millimeter cube, for example. And the power of actually doing that one by one by one is that you can now look at things again in three dimensions in any direction you want. The detail and resolution is perfect.
And so that's what isotropic means. Whereas MRI typically can't be done isotropically just because of time. You want to cover as much as possible, but you want what we call in-plane resolution, which is how you orient the first gradient to have the highest amount of detail. And then you typically will take a perpendicular view. And that's why when you do these rotations off your sagittal plane, the resolution deteriorates wildly in conventional scans, right? Right.
Right, exactly. And so the diffusions that we're doing are done isotropic, but unconventional, not often. So that's why when you rotate, and hopefully in the show notes, we'll be able to get some videos, like we'll literally just show what it looks like. Cause I know this is a
kind of a difficult discussion to have without being able to kind of picture for us. It's easy, but I think we want to make sure that the listener can see this. That's why you don't see any distortion when you rotate the DWI. So is there a commercially available scanner that can do that? Not yet. Someday, not yet. And so basically your goal was just to be, I don't know how to put a timestamp on it. How far are you ahead of what's happening conventionally? I mean, four years ago, you were doing things that I still don't see any scanner doing in the country.
And I see the best scanners. Thank you. But... Well, for example, like when I have a patient that went to one of the most famous hospitals in the country and had a dedicated prostate CT scan, it took 40 minutes just to do the prostate. Dedicated prostate MRI. MRI, not CT, yeah. So he had dedicated prostate MRI, took 40 minutes. It was on a three or four Tesla magnet. And so he spent two thirds of the time to get...
a slightly inferior image by resolution, especially on the DWI, was far inferior to what you were doing on the whole body. It all comes down to basic engineering of signal-to-noise. If you can make all the hardware that you have really sing, your signal-to-noise is so much better. And then you can basically dial it to effectively where you want. So if you need more and more signal, depending on your machine's, I guess, horsepower and coil configuration,
It just takes time. It's always a balance between time and signal to noise. So where is machine learning going to come into the fold here? You actually mentioned something to me recently that I had never thought of, which is it's really hard to throw a whole body image at a machine and have it solve even the simplest problem that we take for granted as a human, which is which one's the liver, which one's the kidney.
And whereas if you weren't doing a whole body, if you were just doing a liver image, that's an easier problem to hand the machine because it already knows it's looking at liver. So, I mean, how far are we away from a machine being able to help you do this? I think that there's actually a lot of tools that actually still need to be written. So for example, part of that is to really kind of look at organs and isolate organs. Conventionally, most imaging is done by body part. So head, neck, chest, abdomen, pelvis, right?
and not connected together. And so when you actually give a machine, okay, here's your brain, it's actually able to kind of go through that relatively efficiently. But part of it really comes down to building the tools to actually analyze whole body. Like even the software to view the whole body is exquisitely complex.
But the difference is that when you actually start to build these tools, it can actually start to help us narrow down what's going on. And the goal is to really sort of have machines make radiologists more efficient. And also, more importantly, we never want to miss anything, right? And so, you know, we can't have a second reader all the time. But if you have a machine being a second reader...
you wind up actually training that machine as you go along. And I think most people would be comfortable with that. And that's what's actually done in mammography right now. And so for, I mean, mammography obviously is like the tip of the iceberg, but you got to start somewhere, right? It's very, I don't want to minimize because I couldn't read a mammogram to save my life, but it's relative to what we're talking about. It's much simpler. It seems that where the machine might first be able to make a dent in what you're doing is not the patient who gets their first scan, but the one who gets the repeat scan. That seems to be
paired t-test seems to be an easier problem to solve and an important problem to solve because a lot of times for us as radiologists like those those studies we still do things the same way when we review them whereas when you actually go and you take like a paired t-test like you said and you actually do a subtraction and where you're looking for the difference or that delta it can actually stand out and become very very simple and very obvious and once that subtraction is done
And I think that's where machine learning will actually really help make us more efficient. And at the end of the day, we just don't want to miss anything. Well, Raj, I've monopolized more of your time today. And that means that there have been probably three or four fewer patients that have been scanned today. So I really appreciate you taking the time. And I appreciate just all the time you've spent over the last
three or four years educating me. You're incredibly generous with your insights and I constantly lob questions at you and you've always got all the time in the world for me and by extension my patients and all the people that I hope to sort of try to educate with this. So thank you for the amazing work you're doing here and then also just for your generosity. Oh, thanks. It's a pleasure. Love it. I need to visit more often. Yeah, next time you come down to California. Sure. We have Uber. Yeah.
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