How MRI Works
It has been a question for me for a while… Let’s look at some references and have a short review:
”]First an explanation from an expert:
Dr. Raymond Damadian, a physician and scientist, toiled for years trying to produce a machine that could noninvasively scan the body with the use of magnets. Along with some graduate students, he constructed a superconducting magnet and fashioned a coil of antenna wires. Since no one wanted to be the first one in this contraption, Damadian volunteered to be the first patient.
When he climbed in, however, nothing happened. Damadian was looking at years wasted on a failed invention, but one of his colleagues bravely suggested that he might be too big for the machine. A svelte graduate student volunteered to give it a try, and on July 3, 1977, the first MRI exam was performed on a human being. It took almost five hours to produce one image, and that original machine, named the “Indomitable,” is now owned by the Smithsonian Institution.
In just a few decades, the use of magnetic resonance imaging (MRI) scanners has grown tremendously. Doctors may order MRI scans to help diagnose multiple sclerosis, brain tumors, torn ligaments, tendonitis, cancer and strokes, to name just a few. An MRI scan is the best way to see inside the human body without cutting it open.
MRI scanners vary in size and shape, and some newer models have a greater degree of openness around the sides. Still, the basic design is the same, and the patient is pushed into a tube that’s only about 24 inches (60 centimeters) in diameter
The biggest and most important component of an MRI system is the magnet. There is a horizontal tube — the same one the patient enters — running through the magnet from front to back. This tube is known as the bore. But this isn’t just any magnet — we’re dealing with an incredibly strong system here, one capable of producing a large, stable magnetic field.
The strength of a magnet in an MRI system is rated using a unit of measure known as a tesla. Another unit of measure commonly used with magnets is the gauss (1 tesla = 10,000 gauss). The magnets in use today in MRI systems create a magnetic field of 0.5-tesla to 2.0-tesla, or 5,000 to 20,000 gauss. When you realize that the Earth’s magnetic field measures 0.5 gauss, you can see how powerful these magnets are.
Most MRI systems use a superconducting magnet, which consists of many coils or windings of wire through which a current of electricity is passed, creating a magnetic field of up to 2.0 tesla. Maintaining such a large magnetic field requires a good deal of energy, which is accomplished by superconductivity, or reducing the resistance in the wires to almost zero. To do this, the wires are continually bathed in liquid helium at 452.4 degrees below zero Fahrenheit (269.1 below zero degrees Celsius). This cold is insulated by a vacuum. While superconductive magnets are expensive, the strong magnetic field allows for the highest-quality imaging, and superconductivity keeps the system economical to operate. Two other magnets are used in MRI systems to a much lesser extent. Resistive magnets are structurally like superconducting magnets, but they lack the liquid helium. This difference means they require a huge amount of electricity, making it prohibitively expensive to operate above a 0.3 tesla level. Permanent magnets have a constant magnetic field, but they’re so heavy that it would be difficult to construct one that could sustain a large magnetic field.
There are also three gradient magnets inside the MRI machine. These magnets are much lower strength compared to the main magnetic field; they may range in strength from 180 gauss to 270 gauss. While the main magnet creates an intense, stable magnetic field around the patient, the gradient magnets create a variable field, which allows different parts of the body to be scanned.
Another part of the MRI system is a set of coils that transmit radiofrequency waves into the patient’s body. There are different coils for different parts of the body: knees, shoulders, wrists, heads, necks and so on. These coils usually conform to the contour of the body part being imaged, or at least reside very close to it during the exam. Other parts of the machine include a very powerful computer system and a patient table, which slides the patient into the bore. Whether the patient goes in head or feet first is determined by what part of the body needs examining. Once the body part to be scanned is in the exact center, or isocenter, of the magnetic field, the scan can begin.
When patients slide into an MRI machine, they take with them the billions of atoms that make up the human body. For the purposes of an MRI scan, we’re only concerned with the hydrogen atom, which is abundant since the body is mostly made up of water and fat. These atoms are randomly spinning, or precessing, on their axis, like a child’s top. All of the atoms are going in various directions, but when placed in a magnetic field, the atoms line up in the direction of the field.
These hydrogen atoms have a strong magnetic moment, which means that in a magnetic field, they line up in the direction of the field. Since the magnetic field runs straight down the center of the machine, the hydrogen protons line up so that they’re pointing to either the patient’s feet or the head. About half go each way, so that the vast majority of the protons cancel each other out — that is, for each atom lined up toward the feet, one is lined up toward the head. Only a couple of protons out of every million aren’t canceled out. This doesn’t sound like much, but the sheer number of hydrogen atoms in the body is enough to create extremely detailed images. It’s these unmatched atoms that we’re concerned with now.
Next, the MRI machine applies a radio frequency (RF) pulse that is specific only to hydrogen. The system directs the pulse toward the area of the body we want to examine. When the pulse is applied, the unmatched protons absorb the energy and spin again in a different direction. This is the “resonance” part of MRI. The RF pulse forces them to spin at a particular frequency, in a particular direction. The specific frequency of resonance is called the Larmour frequency and is calculated based on the particular tissue being imaged and the strength of the main magnetic field.
At approximately the same time, the three gradient magnets jump into the act. They are arranged in such a manner inside the main magnet that when they’re turned on and off rapidly in a specific manner, they alter the main magnetic field on a local level. What this means is that we can pick exactly which area we want a picture of; this area is referred to as the “slice.” Think of a loaf of bread with slices as thin as a few millimeters — the slices in MRI are that precise. Slices can be taken of any part of the body in any direction, giving doctors a huge advantage over any other imaging modality. That also means that you don’t have to move for the machine to get an image from a different direction — the machine can manipulate everything with the gradient magnets.
But the machine makes a tremendous amount of noise during a scan, which sounds like a continual rapid hammering. That’s due to the rising electrical current in the wires of the gradient magnets being opposed by the main magnetic field. The stronger the main field, the louder the gradient noise. In most MRI centers, you can bring a music player to drown out the racket, and patients are given earplugs.
When the RF pulse is turned off, the hydrogen protons slowly return to their natural alignment within the magnetic field and release the energy absorbed from the RF pulses. When they do this, they give off a signal that the coils pick up and send to the computer system.
The MRI scanner can pick out a very small point inside the patient’s body and ask it, essentially, “What type of tissue are you?” The system goes through the patient’s body point by point, building up a map of tissue types. It then integrates all of this information to create 2-D images or 3-D models with a mathematical formula known as the Fourier transform. The computer receives the signal from the spinning protons as mathematical data; the data is converted into a picture. That’s the “imaging” part of MRI.
An MRI scanner applies the radio-frequency field as finely crafted pulses, which excite only protons whose resonant frequencies fall within a fairly narrow range. Applying magnetic-field gradients during the radio-frequency pulse creates resonant conditions for only the protons that are located in a thin, predetermined slice of the body. Orientation and thickness of this slice can be selected arbitrarily in the imaged body. The NMR signal encodes positional information across the slice by using a method known as the “spin warp,” and a two-dimensional Fourier Transform extracts that positional information. The process creates a data matrix in which each element represents an NMR(nuclear magnetic resonance) signal from a single, localized volume element, or voxel, within the imaged slice. A two-dimensional display of this matrix’s contents creates a human-readable image of the selected slice. Each image element, or pixel, represents the NMR signal strength that was recorded for its corresponding voxel.
The MRI system uses injectable contrast, or dyes, to alter the local magnetic field in the tissue being examined. Normal and abnormal tissue respond differently to this slight alteration, giving us differing signals. These signals are transferred to the images; an MRI system can display more 250 shades of gray to depict the varying tissue
. The images allow doctors to visualize different types of tissue abnormalities better than they could without the contrast. We know that when we do “A,” normal tissue will look like “B” — if it doesn’t, there might be an abnormality.
An X-ray is very effective for showing doctors a broken bone, but if they want a look at a patient’s soft tissue, including organs, ligaments and the circulatory system, then they’ll likely want an MRI. And, as we mentioned on the last page, another major advantage of MRI is its ability to image in any plane. Computer tomography (CT), for example, is limited to one plane, the axial plane (in the loaf-of-bread analogy, the axial plane would be how a loaf of bread is normally sliced). An MRI system can create axial images as well as sagitall (slicing the bread side-to-side lengthwise) and coronal (think of the layers in a layer cake) images, or any degree in between, without the patient ever moving.
But for these high-quality images, the patient can’t move very much at all. MRI scans require patients to hold still for 20 to 90 minutes or more. Even very slight movement of the part being scanned can cause distorted images that will have to be repeated. And there’s a high cost to this kind of quality; MRI systems are very expensive to purchase, and therefore the exams are also very expensive.
Magnetic resonance imaging (MRI) devices can scan the inside of the body in intricate detail, allowing clinicians to spot even the earliest signs of cancer or other abnormalities. But they can be a long and uncomfortable experience for patients, requiring them to lie still in the machine for up to 45 min.
Now this scan time could be cut to just 15 min, thanks to an algorithm developed at the Massachusetts Institute of Technology’s (MIT’s) Research Laboratory of Electronics.
MRI scanners use strong magnetic fields and radio waves to produce images of the body. Rather than taking just one scan of a patient, the machines typically acquire a variety of images of the same body part, each designed to create a contrast between different types of tissue. By comparing multiple images of the same region, and studying how the contrasts vary across the different tissue types, radiologists can detect subtle abnormalities such as a developing tumor. But taking multiple scans of the same region in this way is time-consuming, meaning patients must spend long periods inside the machine.
In a paper to be published in Magnetic Resonance in Medicine, researchers led by Elfar Adalsteinsson, an associate professor of electrical engineering and computer science and health sciences and technology, and Vivek Goyal, the Esther and Harold E. Edgerton Career Development Associate Professor of Electrical Engineering and Computer Science, detail an algorithm they have developed to dramatically speed up this process. The algorithm uses information gained from the first contrast scan to help it produce the subsequent images. In this way, the scanner does not have to start from scratch each time it produces a different image from the raw data, but already has a basic outline to work from, considerably shortening the time it takes to acquire each later scan.
To create this outline, the software looks for features that are common to all the different scans, such as the basic anatomical structure, Adalsteinsson says. “If the machine is taking a scan of your brain, your head won’t move from one image to the next,” he says. “So if scan number two already knows where your head is, then it won’t take as long to produce the image as when the data had to be acquired from scratch for the first scan.”
In particular, the algorithm uses the first scan to predict the likely position of the boundaries between different types of tissue in the subsequent contrast scans. “Given the data from one contrast, it gives you a certain likelihood that a particular edge, say the periphery of the brain or the edges that confine different compartments inside the brain, will be in the same place,” Adalsteinsson says.
However, the algorithm cannot impose too much information from the first scan onto the subsequent ones, Goyal says, as this would risk losing the unique tissue features revealed by the different contrasts. “You don’t want to presuppose too much,” he says. “So you don’t assume, for example, that the bright-and-dark pattern from one image will be replicated in the next image, because in fact those kinds of dark and light patterns are often reversed, and can reveal completely different tissue properties.”
So for each pixel, the algorithm calculates what new information it needs to construct the image, and what information—such as the edges of different types of tissue—it can take from the previous scans, says graduate student and first author Berkin Bilgic.
The result is an MRI scan that is three times quicker to complete, cutting the time patients spend in the machine from 45 to 15 min. This faster scan time does have a slight impact on image quality, Bilgic admits, but it is much better than competing algorithms.
The team is now working to further improve the algorithm by speeding up the time it takes to process the raw image data into a final scan that can be analyzed by clinicians, once the patient has stepped out of the MRI machine. Using standard computer processors, this final step currently takes considerably longer than with conventional MRI scans.
But the researchers believe they can reduce this calculation time down to the same as that of conventional MRI scans using recent advances in computing hardware from the gaming industry. “Graphics processing units, or GPUs, are orders of magnitude faster at certain computational tasks than general processors, like the particular computational task that we need for this algorithm,” Adalsteinsson says.
A student at the laboratory is now working to implement the algorithm on a dedicated GPU, he says.
MRI machines are evolving so that they’re more patient-friendly. For example, many claustrophobic people simply can’t stand the cramped confines, and the bore may not accommodate obese people. There are more open scanners, which allow for greater space, but these machines have weaker magnetic fields, meaning it may be easier to miss abnormal tissue. Very small scanners for imaging specific body parts are also being developed.
Other advancements are being made in the field of MRI. Functional MRI (fMRI), for example, creates brain maps of nerve cell activity second by second and is helping researchers better understand how the brain works. Magnetic resonance angiography (MRA) creates images of flowing blood, arteries and veins in virtually any part of the body. I will post a topic about fMRI soon…