Diffusion tensor imaging, or diffusion-weighted magnetic resonance imaging (DW-MRI), is an imaging technique based on classical MRI that images the diffusion behavior of water molecules in biological tissue. It is mainly used for examinations of the brain. Analogous to classical MRI, the procedure is noninvasive and does not require the use of ionizing radiation.
What is diffusion tensor imaging?
In clinical practice, diffusion tensor imaging is mainly used to study the brain because its diffusion behavior allows conclusions to be drawn about some diseases of the central nervous system. Diffusion-weighted magnetic resonance imaging is a magnetic resonance imaging (MRI) technique that measures the diffusion motion of water molecules in body tissues. In clinical practice, it is mainly used to examine the brain, because the diffusion behavior of water allows conclusions to be drawn about some diseases of the central nervous system. With the help of diffusion-weighted magnetic resonance imaging or diffusion tensor imaging, information about the course of the large nerve fiber bundles can also be obtained. Commonly used diffusion tensor imaging (DTI), a variant of DW-MRI, also captures the directionality of diffusion. DTI calculates a tensor per unit volume, which is used to describe the three-dimensional diffusion behavior. However, these measurements are significantly more time-consuming than classical MRI due to the immense amounts of data required. The data can only be interpreted through the use of various visualization techniques. Today, diffusion tensor imaging, which originated in the 1980s, is supported by all new MRI machines.
Function, effect, and goals
Like conventional MRI, diffusion-weighted MRI is based on the fact that protons have a spin with a magnetic moment. The spin can align to an external magnetic field either parallel or antiparallel. In this case, the antiparallel alignment has a higher energetic state than the parallel alignment. Thus, when an external magnetic field is applied, an equilibrium is established in favor of the low-energy protons. If a high-frequency field is switched on transversely to this field, the magnetic moments flip in the xy-plane direction depending on the strength and duration of the pulse. This condition is called nuclear spin resonance. When the radiofrequency field is turned off again, the nuclear spins realign toward the static magnetic field with a time delay that depends on the chemical environment of the proton. The signal is registered via the voltage generated in the sensing coil. In diffusion-weighted magnetic resonance imaging, a gradient field is applied during the measurement, which changes the field strength of the static magnetic field in a predetermined direction. This causes the hydrogen nuclei to go out of phase and the signal to disappear. When the direction of rotation of the nuclei is reversed by another high-frequency pulse, they get back into phase and the signal appears again. However, the intensity of the second signal is weaker because some nuclei no longer come into phase. This loss of intensity of the signal describes the diffusion of the water. The weaker the second signal is, the more nuclei have diffused in the direction of the gradient field and the lower is also the diffusion resistance. However, the resistance to diffusion in turn depends on the internal structure of the nerve cells. Thus, with the help of the measured data, the structure of the examined tissue can be calculated and visualized. Diffusion-weighted magnetic resonance imaging is frequently used in stroke diagnosis. Due to the failure of the sodium–potassium pumps in stroke, there are severe limitations in diffusion motion. This becomes immediately visible with DW-MRI, whereas with conventional MRI the changes can often only be registered after several hours. Another area of application relates to surgical planning during brain surgery. Diffusion tensor imaging establishes the course of the nerve pathways. This must be taken into account during surgical planning. Furthermore, the images can also show whether a tumor has already invaded the nerve pathway.This method can also be used to assess whether an operation is at all promising. Many neurological and psychiatric diseases, such as Alzheimer’s disease, epilepsy, multiple sclerosis, schizophrenia or HIV encephalopathy, are now the subject of diffusion tensor imaging research. The question is which brain regions are affected in which diseases. Diffusion tensor imaging is also increasingly being used as a research tool for cognitive science studies.
Risks, side effects, and hazards
Despite its good results in the diagnosis of strokes, in the preparation of brain surgery, and as a research tool in many clinical trials, diffusion-weighted magnetic resonance imaging still encounters limitations in its application today. In some cases, the technique is not yet fully developed and requires intensive research and development to improve it. For example, diffusion-weighted magnetic resonance imaging measurements often provide only limited image quality because diffusion motion is manifested only by attenuation of the measured signal. Little progress has also been made with higher spatial resolution, because with smaller volume elements the signal attenuations disappear in the noise of the measurement apparatus. In addition, a large number of individual measurements are necessary. The measurement data must be reprocessed in the computer in order to be able to correct disturbances to some extent. Up to now, there are also still problems to represent a complex diffusion behavior satisfactorily. According to the current state of the art, diffusion within a voxel can only be recorded correctly in one direction. Methods are being tested that can simultaneously take diffusion-weighted images in different directions. These are methods that require high angular resolution. The methods for evaluating and further processing the data also still require optimization. For example, previous studies compared data obtained from diffusion-weighted magnetic resonance imaging from larger groups of subjects. However, due to the different anatomical structures of different individuals, this can lead to misleading study results. Therefore, new methods for statistical analysis also need to be developed.
