Salute to Röntgen: 100 Years of Internal Imaging
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Professor Fine and Dagen, thank you for that introduction. And to everybody else here, let me say, particularly Countess Sonia, what a great pleasure it is to come to Lindau and meet old friends and then also meet new Nobel Prize winners
00:46
who may be not so young or not so old, but the main focus of this place I think really is on the students, and it's very nice to make friends there. I, too, Sir Andrew, will have some examples of scientific forgetfulness in my talk which
01:05
will come up in a little while. First slide, please. This is perhaps the most famous X-ray ever made. It's the hand of Professor Roentgen's wife. And you probably saw it a lot last year during the celebrations of the centenary of Roentgen's
01:28
discovery of X-rays. I'm showing it again because it's a natural prelude to my talk, but it is also a prelude to all of what is now called modern physics.
01:46
Whatever X-rays contributed to imaging in medicine, we must never forget that the discovery of X-rays was the first step in the replacement of classical physics by what is now called modern physics, even though it's no longer very modern.
02:05
As Minister Gopel pointed out, Roentgen's discovery in 1895 was followed by Becquerel's in 1896, by the discovery of the electron by J.J. Thompson in 1897, of Planck's discovery
02:23
of photons in 1900, Einstein's special relativity in 1905, and a host of other discoveries. These all set the stage for the development of the quantum mechanics of 1925, which governs the physics of the 20th century, and which still produces indisputable proofs that some
02:47
of our dearest held ideas of what constitutes common sense no longer seem to be very sensible. Now Roentgen's choice of his wife's hand to X-ray was very simple.
03:03
It showed how a special approximately flat or sliced through the particular part of the human body showed much detail. But if the hand, instead of being like this, had been rotated through 90 degrees,
03:20
the picture would have produced a very confused image because the images of all the fingers would have been superposed. This is illustrated in the next slide. Imagine we want to take an X-ray of this head here from the left. Imagine the head cut up into a lot of various slices like this, but in fact many
03:45
more than I've shown in the slide. Then you see each slide, each slice by itself, would have produced a nice image on the film. But when you put them all together, they produce a great mess and you wouldn't get
04:02
a very different picture, X-ray picture, if you took all the slices and shuffled them like a deck of cards because you lose all sense of depth in the X-rays. So I suggest that the necessity for getting pictures of slices through the body must have
04:23
been obvious right from the year 1895 on. However, it was only around 1920 that these were developed in what I called mechanical tomography. Next slide, please. And here the X-ray tube and the film are moved together so that the image of one slice,
04:50
just the slice called the focal plane here, stays the same in the same position on the film and so produces a fairly sharp image.
05:01
But as the equipment moves, the slices above and below the focal plane move relative to the film and the film becomes blurred. Amazingly intricate pictures, devices were developed until about 1970 by people like
05:21
Takahashi in which the X-ray tube was moved and the patient was moved and the film was moved. Sometimes they were all rotating together and the images they produced, which were called tomograms, were not very good, but they were better than nothing up to that
05:41
time. I think there's a slide missing. Could you just check to see if there's not a double slide there? Well, it'll have to do without that one. I grew up in South Africa and I went to school and to college and so on in Cape
06:08
Town and near the university and also near the hospital. And after graduate work in nuclear physics at Cambridge, England, I returned to the University
06:22
of Cape Town to teach physics. The slide that I was going to have shown shows the Croesus Hospital, which features in the story and was also the place where Dr. Christian Barnard did the first heart transplant. The old part was built about 50 years ago and has just been replaced by a modern hospital.
06:46
It was just by chance that I got interested in X-ray imaging. In 1956, the hospital physicist of the Croesus Hospital, and in those days there was only one, resigned.
07:00
I was the only person in Cape Town and I think all of South Africa who knew how to handle radioactive isotopes and so on, so I was asked to spend a day and a half a week at the hospital doing the essential part of the work of the hospital physicist. There was no medical physics department then, so I was put in the radiotherapy department
07:25
where I saw how radiation treatments were planned. And as a physicist, I was kind of horrified by what I saw. The physicians, the radiologists, used these devices like this called isotope...isodose
07:45
charts which give you, starting at the top with 100%, the dose in decreasing percentages for different values of the X-ray energy, 200 kilovolts. This is about 1.3 megavolts, and then here's 25 MeV, which is more like the modern X-ray
08:09
energies. Now, these showed or show what dose of radiation would be delivered to a homogeneous medium like a block of wax or a tank of water, but I thought that there would be
08:25
very little use in, for example, a beam into a patient's chest where some of the X-rays pass through the bone, which have heavy absorption, some through muscle, which have less absorption, and some through lung tissue, which has even less absorption.
08:48
So all of these things absorbed X-rays differently. The problem then was much more acute than it is now because people then use much lower energies like this than the energies over here.
09:05
So my thought was that in order to plan treatments properly, one needed some kind of map of absorption of X-rays by the various tissues of the body on planes through the body. And this had to be found from measurements made outside the body.
09:25
The next slide, you know the mathematics shows what I mean. You can measure this intensity, I0, of X-rays incident along a line through the head here, and you can measure the emerging intensity there, and from that you can calculate the
09:42
average absorption along that line, L. And the question that came up was the following. If we do this for a lot of lines which intersect the head or body or whatever this
10:00
is, can you from this then deduce how the X-ray absorption varies from one point to another in the head? We can illustrate this problem in the following simple way. Next slide, please.
10:21
Here is a map of an island in the ocean. See, there's a mountain here, a mountain here, and a bay in between them. If we take a section through that island along the line AB, it'll look something like this. Here's one mountain, here's the other mountain, here's the bay in between them. Now if we have a graph like this of the height, we can of course easily calculate the average
10:46
height of the island along that line. Now I don't know how to do it, I don't think anybody does, but the question pertinent here is if we knew by some magical means the averages of all lines across the island,
11:06
could we then deduce actually the contour map of the island? And the answer is yes, and I'm not going into the details at all because many algorithms
11:20
are now known for doing so. But being unaware and forgetful, to use Professor Huxley's phrase of what had gone before, I had to start ab initio. In 1957 I moved to the United States and I was busy with other research and teaching.
11:41
So it was before, it was 1963 before I built my first scanner to test my theories. And the next slide shows it. It cost about $100 to make in the machine shop. These two brass cylinders just form a very fine beam of x-rays which pass through this
12:04
phantom of a head here. The aluminum ring around the outside represents the skull. There are two aluminum plugs in it which show two supposed tumors. And by rotating this and translating it backwards and forwards, one can measure the average
12:25
absorption along many lines through the head and so get a map of the absorption coefficient in this section of the head. And the results are shown in the next slide.
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Here is the phantom, aluminum ring representing the skull. Here are the two tumors, also aluminum blocks. And this is the leucite. And here is, I didn't think of displaying this on a scope, but along this line OA, here
13:01
is the experimental results of these dots and the straight line represents the actual values of the aluminum absorption and you can see there's a fair match. Here's the inner, here's the inner tumor, here's the main tumor here and here's
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the skull out at the edge. You see there's some wiggles on here which I had hoped to remove. There are standard methods for removing them. But I had all the computation done by an undergraduate so that he could learn Fortran at this time
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and the trouble with having undergraduates write programs for you is that they graduate and go away and then nobody can use their programs afterwards. So I never got rid of the wiggles. Anyhow, as Professor Feynman-Dagan said, I got only three responses to my publication
14:04
which was in those days very disappointing because this was before Xerox machines were invented. Nowadays nobody writes for reprints, they just Xerox the stuff that they want, but before the Xerox machine is the number of reprints you got asked for, some measure of how much
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interest there was in your paper. But any case, I had a lot of other things to do so I went ahead with them and I almost forgot the whole matter. It was only about 1970 that I started hearing about a machine developed by Hounsfield in
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England called the EMI scanner which could be used for heads only but which did in the clinic what I was hoping my device would have done when reduced to a practical form. And with the EMI scanner, radiologists were for the first time seeing clearly what previously
15:03
they had mostly guessed at or found through exploratory surgery. And they went wild about it and soon a thriving industry developed to supply the enormous demand for what we now call CAT scanners. Now you've all seen CAT scans and many of you may have had them, so I'll just show
15:23
you one but I'd like to go away from just medical applications in these things that I'm going to talk about because actually many interesting applications of them are in other fields. So the next slide shows the kind of unusual patient that you can deal with here.
15:42
This is a very famous person who was a very famous person. She's actually got a name, not just a museum number, and she's called Mrs. Pless. And she and her relatives roamed the savannah of Africa about two million years ago. And we have probably all descended from her and her family.
16:08
And the point that I want to make here is that even though she's now all fossilized and stoned, you can modify an x-ray tube fairly easily to take CAT scans of it.
16:24
And the next slide shows a CAT scan somewhere in the neighborhood of the ear. You can see here's the entrance to the ear here. And these are the semicircular canals here. And in fact, from the orientation of these semicircular canals relative to the axis
16:43
of the head, one can verify that Mrs. Pless and her family walked around upright and not like a baboon on four legs. This had, I should say, previously been established by traditional anthropological methods.
17:01
Now without going into technical details, just let me show you a couple of examples of different kinds of maps which can be obtained by tomographic methods. The next slide shows a map of the sun, of the moon, I mean, by reflected microwaves
17:22
at 9.1 centimeters. And this was done by Bracewell in Australia just about the time as I started working on this in Cape Town. He was using an array of radar detectors which act like a cylindrical lens and sort
17:40
of averages over lines across the moon. The next slide shows a map of the temperature of the sea on a scale of kilometers. See, this is 0 to 300 kilometers, this is 0 to 300 here. By measuring the time of transmission of sound waves through the water and using the
18:10
fact that the velocity of sound depends on the temperature, you can deduce a map of the temperature and here these are the temperatures relative to some standard 0, minus 1, minus
18:21
2, minus 3, plus 1, plus 2, plus 3, plus 4, and so on. And there are many, many applications these days of these tomographic methods. Now next on my list of medical imaging modalities is something which is called PET scanning, or positron emission scanning.
18:42
And along with the discovery of X-rays by Roentgen and the three applications I'm going to discuss, all three stemmed from discoveries in physics which earned their discoverers Nobel Prizes. Roentgen got the first Nobel Prize in physics in 1901, and in the same year I
19:07
guess Heisenberg, Dirac got his prize, his Nobel Prize in physics, because he produced a relativistic theory of the electron.
19:22
And this predicted that there should be, corresponding to the electron, a little particle of the same mass, but the opposite charge, which is now called a positron. There's only one problem. Nobody knew anything about positrons at that time, and the only positive particle they
19:40
knew was the nucleus of the hydrogen atom, which was a proton. But unfortunately, that differed in mass from the electron by a factor of 2,000. Anyhow, in about five years, positrons showed up in cosmic radiation. And then with the advent of the discovery of artificial radioactivity, they found they
20:05
could be produced there. And so it's easy to get hold of positrons nowadays, and Dirac's theory was in fact verified in great detail. The next slide shows what happens if you have a positron, E plus here to indicate
20:23
its positive charge, and an electron, both starting from rest, and then of course being attracted together because they're of opposite charge. If they're initially at rest, their total linear momentum must be zero, and so from the conservation of linear momentum, the system, whatever happens to it, must still
20:45
have zero momentum. And when these come together, they disappear in a flash of electromagnetic radiation, and because light photons, a quanta of light, carry momentum as well as energy,
21:04
you have to produce two of them going in exactly opposite directions with exactly opposite momenta, so that the total momentum, which is the vector sum of those two, is zero. The next slide shows how one detects these things.
21:23
If a positron annihilates here and one photon goes into this thing, another photon goes here, and if we connect this to something which counts coincidences, we measure something which measures the average rate of annihilation of positrons in this column
21:43
connecting the two detectors, and in the limit, this is a line, and so we're back to this problem of if we move these detectors around in different lines, can we from these average values deduce the variation of distribution of the positron emitting material in this,
22:06
for example, a head. The next slide, please, shows how this is applied. This is a rather old picture nowadays of this PET scanning. Here the patient has been fed glucose, which has been labeled with fluorine-19, and these
22:27
pictures show as a function of time how the activity in the brain changes, and the changes represent the places where the positrons have gone.
22:47
Now, it's in PET scanning, I believe, that people first started thinking about what is now called functional imaging, which is becoming of increasing importance in research
23:01
if not in routine clinical diagnosis. If you scratch the left hand of a patient undergoing a PET scan, then a part of the patient's brain which processes information about feelings in the left hand will light up because of an increase in its metabolic rate.
23:24
Hence, you can associate the activities of various parts of the brain with some function of the human body. Of course, at first, this just confirmed what physiologists already knew, that is that some human functions were handled by specific regions of the brain, but I think already
23:46
functional imaging with PET and others that I'll mention is enlarging our knowledge of this field. Now so far, I've talked about maps just in two dimensions, such as the examples I showed you of temperature distributions and so on.
24:04
And I'd like to generalize this in two ways. One is to go from two dimensions to three dimensions, and the other is to go from ordinary spaces to some that are more abstract.
24:21
And if in three dimensions, what happens is that we replace averaging along lines by averaging over planes, as is shown in the next slide. Let the circle now here represent, say, a three-dimensional sphere, and let this represent
24:40
a disk cut out of the sphere. We can average over this surface and lots of other surfaces intersecting the sphere. And the answer is, can we find out the distribution of whatever it is we're averaging from this knowledge? And the answer is, again, yes. And strangely enough, it's easier to do it in three dimensions than in two dimensions.
25:08
This is, in fact, the first form in which this problem was investigated. And now we get to the bit about people forgetting in science. Because this problem of working from the averages over planes to the local distribution
25:25
was done before 1905 by the great Dutch physicist H.A. Lorentz. We don't know why he studied this because he didn't even publish his results. The only reason we know of his work is that a student of his stated that Lorentz
25:43
had discussed this problem in some lectures. He applied the solution of the problem, which he published in 1905. It was only 12 years later in 1917 that an Austrian mathematician called Radon published
26:00
the two and three-dimensional forms of the problem. And for that reason, it is now called Radon's problem, not just for two reasons or three reasons but not for just two dimensions or three dimensions but for any number of dimensions. Now, let us introduce a more abstract space as it occurred historically.
26:23
And in 1936, 31 years after Lorentz, 19 years after Radon, 20 years before my work, provides us with the first application of the problem, not in radiology but in astronomy.
26:41
There are many stars in the neighborhood of the sun, and they are moving around in all kinds of directions with all kinds of speed. In the 1930s, astronomers were interested in finding how these velocities were distributed. The simplest way of describing this is to set up an imaginary space in which each star
27:06
is represented by a vector, the length of which represents the speed of the star, and the direction, of course, gives the direction of motion. And you can think of this as being some kind of origin with all these arrows sticking out of it, and this is what we call a vector space.
27:24
The problem is how to detect the ends of these vectors distributed throughout the volume. And here we encounter a difficulty. The next slide shows this. Suppose we're looking in this direction towards a star, then the star has two components
27:41
of velocity, one along what's called the line of sight towards the star, one at right angles to that, which is called by astronomers the proper motion. The actual velocity, which we want to find, is this thing here. Now, it's easy to find the components along the line of sight, or the radial velocity,
28:03
from the Doppler effect, which gives the shift of the spectrum, and from that we get this velocity. But there are very few stars which are moving fast enough or are now close enough to the sun to make this proper motion at all observable.
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And so the problem is how do you deduce the direction of the actual velocity vectors like that, knowing only the components along the line of sight. If you think about this carefully, you will see that all the stars in a particular direction
28:45
in space with the same velocity shift lie on a plane in the three-dimensional space of velocities of the stars. The next line shows the results that Ambar Tsoumian, who is the man who did this
29:01
work, published, and this is to be interpreted in the following way. This is a projection of this distribution of velocity vectors onto the galactic plane, and this number 22 here says that there are 22 stars with a velocity vector starting
29:21
at the figure 6 there and going to 22. And here there might be six stars with a velocity vector in this direction and so on. Negative stars aren't to be taken seriously. There is a result of noise in the data. Now I wouldn't have known about this work of Ambar Tsoumian's if he hadn't written
29:45
to me shortly after I received my prize. And in his letter he said, about six months after I published this paper, a mathematician came up to me and said, didn't you know that Radon had solved this problem about 20
30:01
years ago? Another example of Professor Huxley's forgetfulness. I'm sorry, his lecture on forgetfulness, not his forgetfulness. Using planes in three dimensions is also a very natural way of looking at the last medical imaging problem that I will discuss, namely magnetic resonance imaging.
30:22
I hasten to add that it is not necessarily the algorithm used in commercial MRI machines. The story begins with the discovery of the phenomenon called nuclear magnetic resonance by Bloch and Purcell for which they received the Nobel Prize in 1952.
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The phenomenon occurs because some, but not all, nuclei are little spinning balls of charge. So they behave like little bar magnets. When they're in a magnetic field, they tend to line up with the field, but they
31:02
also precess around the direction of the field like a top spinning on its point. And they do this with a characteristic frequency which depends on the strength of the field and the strengths of the little bar magnets which are characteristic of each nuclear species. If they are irradiated with microwaves of just the right frequency, they flip to
31:26
a different state by absorbing a photon of the incident radiation, and a little later they flip back to their original state emitting a photon of the same frequency. This absorption and subsequent emitting is known as nuclear magnetic resonance, but the
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word nuclear has been dropped because a lot of people now believe it to be a dirty word. And so we now have, instead of nuclear magnetic resonance imaging, just magnetic resonance imaging. When I was just starting out in physics, the main precaution one had to take to get any
32:01
NMR signal at all was to have a highly uniform magnetic field. Then the resonance frequency would be the same throughout the sample, and so you'd get a fairly strong image from the sample. This shows the typical case up here of a sample with a uniform field across it, and
32:24
all resonance takes place at the same frequency throughout the sample, and so you get a big signal. Now, the technology of magnetic resonance increased over the years, and it occurred
32:41
to, about 1972, it occurred to Paul Lauterbur that by applying a very small gradient of a field, that is a field plus a small linear variation of the field, would produce a resonance signal which was confined to the plane in the sample. So there'd only be one frequency for which resonance occurred in that plane.
33:05
And by changing the frequency and the direction of this gradient G, capital G, he could sample over many planes, and by hey presto, by the distribution of magnetism in the sample could be found using the Ambot-Soumian or Lorentz results in three dimensions.
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In fact, Lauterbur used two gradients which define two planes which intersect in the line, and then he used the two-dimensional algorithms from CT. And this is what led to the development of magnetic resonance imaging.
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Most commercial MRI machines look at the protons, that is the nuclear hydrogen atoms, which are plentiful in the human body, which of course is mostly water. The alignment of the protons along the direction of the magnetic field is very slight. Only about one in 100,000 protons on average being lined up with the magnetic field.
34:07
Despite this, MRI gives good images, and one of the early images, which is poor by comparison with the present, is shown in the next slide. Here's the skull around the outside, and here are the details inside.
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You don't see too much in the skull because calcium does not undergo magnetic resonance, and so you don't see it in the body. The reason I show this particularly is that this is something like 15 centimetres across here, 10 centimetres. That's the sort of scale on which you think of magnetic resonance imaging occurring.
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However, there have been recent developments in several directions. One of these is, three directions I'm going to mention, one of these is microscopy, two, the use of spin polarized gases, and three, functional images, which I mentioned earlier,
35:04
in connection with PET scanning. Now, the next slide shows an example of the cochlea of a bat, which is a pretty, you know, a bat's a pretty small creature to begin with, and its ear is even smaller.
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So the scale of this thing here is one millimetre rather than 15 centimetres. So you see we're getting to see quite small features in this MRI microscopy. This slide was a little bit of mild embarrassment to me when I showed it in Wurzburg last November
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at the Röntgen celebrations because I thought this was creating some sort of record because these details in here are on a scale of about 10 microns, whereas when I got to Wurzburg
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I found that Professor Hasse there had already got a resolution of about 5 microns and that was in November, things are moving fast, so the present resolution is probably down to about 1 micron, and it's getting smaller all the time.
36:21
Now, as I mentioned, the amount of magnetisation in regular MRI is very small, only about one proton in 100,000 being lined up with the magnetic field. However, by a process known as spin polarisation, some of the nuclei of some gases can have
36:44
as many as four out of five nuclei all lined up in one direction, and so they are magnetised about 100,000 times as much as the hydrogen in the body. Two of these are Helium-3 and Xenon-129, which are both noble gases which can safely
37:06
be inhaled. The last slide, please, shows the lungs of a mouse, again a pretty small object, obtained by Dr Johnson at Purdue and Dr Happer and his co-workers at Princeton.
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This is what would show up with ordinary MRI, even on a somewhat microscopic level. This one here looks like a worse image, but in fact, all this graininess here is in fact further detailed and shows the actual distribution essentially of cavities in the lung where
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there's a concentration of these spin-polarised gases. The fact is that the factor of 100,000 increase in polarisation of the spin-polarised gases can offset the difference in density between a gas and, say, water of about a
38:04
thousand and still give you a strong image. That is not the end of the story. The polarised gases that are in the lungs here can in fact parse their polarisation and spin onto other atoms in the lung.
38:28
Those can then be looked at with a different frequency of MRI and studied as a consequence of their being formed from something, these helium or xenon in the lung.
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And that's because these little bar magnets, as I mentioned, have frequencies which are characteristic of the atoms which are in fact polarised. Now I leave it to your imagination to think of applications for this if you go from the
39:00
spin-polarised gas to other atoms, and I'll end simply by saying that the revolution in imaging, which Roentgen started, is still vigorously going on. Thank you.