What is Diffusion Tensor Imaging?

Diffuse tensor imaging (DTI) is a new way to describe the structure of the brain and is a special form of magnetic resonance imaging (MRI). For example, if nuclear magnetic resonance imaging is tracking hydrogen atoms in water molecules, diffusion tensor imaging is mapping based on the moving direction of water molecules. Diffusion tensor imaging (presented differently from previous images) can reveal how brain tumors affect nerve cell connections and guide medical staff to perform brain surgery. It can also reveal subtle abnormalities related to stroke, multiple sclerosis, schizophrenia, and dyslexia.

Chinese name: Diffusion tensor imaging

Foreign name: diffusion tensor imaging, DTI
profession: Special MRI technology

Introduction to diffusion tensor imaging

Diffusion refers to the random and irregular movement of molecules, an important physiological activity of the human body, and one of the ways of transporting substances in the body, also known as brownian motion. Diffusion is a physical process whose primary motive force is the thermal energy possessed by the molecule. In solution, the factors that affect the dispersion of a molecule are: the weight of the molecule, the interaction between the molecules (that is, the viscosity), and the temperature.

Diffusion is a three-dimensional process. The distance that molecules diffuse in one direction of space is equal or unequal. There are two ways of dispersion: one is that in a completely uniform medium, the movement of molecules is The distances in the direction of movement are equal. This type of dispersion is called isotropic dispersion. For example, the diffusion of water molecules in pure water is isotropic dispersion. In human brain tissue, the cerebrospinal fluid and water in the brain gray matter Molecular diffusion is approximately isotropic. Another type of dispersion has a direction dependence. In tissues arranged in a certain direction, the molecules diffuse in different directions in different directions are called anisotropic dispersion.

Diffusion tensor imaging (DTI) is the development and deepening of diffusion weighted imaging (DW I), and it is currently the only non-invasive examination that can effectively observe and track the white matter fiber bundles in the brain. method. By 2015, it is mainly used for the observation and tracking of white matter bundles in the brain, the study of brain development and brain cognitive function, the pathological changes of brain diseases, and the preoperative planning and postoperative evaluation of brain surgery. Diffusion imaging

In magnetic resonance imaging. Tissue contrast is not only related to the T1, T2 relaxation time and proton density of the tissue in each pixel, but also to the diffusion of water molecules in each pixel of the tissue under test. Hahn first proposed the effect of water molecules on magnetic resonance signals in 1956.

The dispersion process can be measured with a dispersion-sensitive gradient magnetic field. When the gradient magnetic field is applied, the random movement of water molecules can obtain a random displacement, which causes refocusing and loss of phase, and the spin echo signal decays. In 1965, Stejskal and Tanner designed the gradient magnetic field spin echo technology. A dispersion sensitive gradient magnetic field was applied before and after the 180o pulse of the spin echo sequence to detect the dispersion of water molecules. The value for measuring the dispersion is called the dispersion coefficient, which is represented by D, that is, the average range of free and random dispersion motion per unit time of a water molecule, the unit is mm2 / s. The larger the D value, the stronger the diffuse motion of water molecules. Can be described by the formula ln (S / S0) =-bD. D is the diffusion coefficient, and S and S0 are the signal strengths with and without the gradient magnetic field applied, respectively. b is the dispersion sensitivity coefficient, b = 2G22 ( - / 3). rotation ratio, Ggradient field strength, application time of each gradient pulse, pulse application time interval. The value b is constant and is controlled by a parameter of the applied gradient field strength. The larger the value of b, the more sensitive it is to the diffuse motion of water molecules, which can cause greater signal attenuation.

The dispersion process can be measured with a diffusion-sensitive gradient magnetic field In the human physiological environment, the D value is affected by many factors, so the apparent diffusion coefficient (ADC) is commonly used to measure the diffusion movement of water molecules in the human tissue environment, that is, all factors that affect the movement of water molecules (random And non-random) are superimposed into an observation value that reflects the displacement strength of water molecules in the direction of the dispersion-sensitive gradient. According to the Stejiskal-Tanner formula, ADC = ln (S2 / S1) / (b1-b2), S2 and S1 are the signal strengths under different b-value conditions. Magnetic resonance DWI uses ADC value distribution imaging. The higher the ADC value, the stronger the diffuse motion of the water molecules in the tissue, which appears as a low signal on the DWI map. Conversely, the lower the ADC value, the higher the signal on the DWI map.

^{[1] The} apparent dispersion coefficient ADC only represents the dispersion characteristics of water molecules in the direction of the application of the dispersion gradient magnetic field. It is impossible to evaluate the anisotropy of different organizations completely and correctly. Higano et al. Applied a diffusion gradient magnetic field to the X-, Y-, and Z-axes when studying the anisotropy characteristics of the inner capsule and radiation crown in patients with stroke and brain tumors. However, the research results show that the degree of tissue anisotropy calculated by three-direction diffusion-weighted imaging is often underestimated, and the measured value is often a rotation variable (that is, the value changes with the direction of dispersion and the position and orientation of the patient under examination in the magnetic field) Because most white matter fiber pathways are often tilted in the direction of the magnetic field coordinates, the application of a dispersive gradient magnetic field from one or three directions alone cannot correctly evaluate the anisotropic characteristics of an asymmetric tissue structure.

feature

Fiber tracking technology DTT Evaluation of diffusion anisotropy along the fiber direction requires diffusion tensor imaging. Therefore, people have proposed the concept of a diffusion tensor. The term "tensor" comes from the fields of physics and engineering. It uses a set of 3D vectors to describe the tension in solid matter. The diffusion tensor is determined by the following formula:

This tensor is symmetric (Dxy = Dyx, Dxz = Dzx, Dyz = Dzy). In order to visualize the diffusion tensor, we can further treat the diffusion tensor as an ellipsoid. The eigenvalues represent the dispersion coefficients along the maximum and minimum axes of the dispersion ellipsoid. The three eigenvalues of the diffusion tensor are the most basic rotational invariants (that is, the values do not change with the direction of the dispersion and the position and direction of the patient being examined in the magnetic field). They are the main dispersion coefficients measured along the three axes . These three coordinates are inherent to the organization, and each eigenvalue is associated with an eigenvector of a principal direction, and this eigenvector is also inherent to the organization.

The three eigenvectors of the diffusion tensor are perpendicular to each other, and a local reference fiber frame is constructed for each pixel. In each voxel, the eigenvalues are arranged from large to small: 1 = maximum dispersion coefficient, 2 = intermediate dispersion coefficient, 3 = lowest dispersion coefficient. 1 represents the dispersion coefficient parallel to the fiber direction, and 2 and 3 represent the lateral dispersion coefficient.

Basic Principles of Diffusion Tensor Imaging

Anisotropy

Diffusion is a kind of random, collision and transcendence movement of material molecules in nature, that is, Brownian motion. The dispersion of free molecules in pure liquid is isotropic. The average distance of dispersion is only related to the properties of liquid molecules and the average temperature. The dispersion coefficient is used to measure the average free path of free molecules in the liquid (unit: mm) ² / s). Water molecules in brain tissue are constantly undergoing diffuse motion, but it is not only affected by the characteristics of the tissue cells themselves, but also by the internal structure of the cells, such as sheath membranes, cell membranes, and white matter fiber bundles. In a tissue structure with a fixed arrangement order, such as nerve fiber bundles, the diffusion of water molecules in different directions is different. ^[2] Water molecules are generally more inclined to diffuse along the direction of nerve fiber bundles, and Diffusion is rarely performed in a direction perpendicular to the nerve fiber bundle. This direction-dependent dispersion is called diffusion anisotropy.

Magnetic resonance diffusion weighted imaging (DWI)

DWI ^[4] is a newer technique for measuring the microscopic random displacement motion of spin protons. By 2015, it will mainly measure the motion of water molecules. Its image contrast is mainly related to the displacement motion of water molecules. It is usually Obtained on a standard MRI sequence with gradient-sensitive gradient pulses. The motion characteristics of water molecules can be expressed by the apparent dispersion coefficient ^[5] (apparent diffusion coefficient ADC) in the direction of the dispersion-sensitive gradient. The ADC value is a scalar quantity, which only represents the dispersion characteristics of water molecules in the direction of the application of the dispersion gradient magnetic field, and cannot completely and accurately evaluate the characteristics of anisotropy of different tissues.

Diffusion Tensor Imaging (DTI)

DTI is an advanced form of diffusion imaging ^[6] that can quantitatively evaluate the anisotropy of white matter in the brain (Figure 1). In this imaging method, no

Figure 1 DTI image showing white matter fiber bundles Only a single gradient pulse is used, and at least 6 non-collinear directions are required to diffuse the sensitive gradient. The simplest solution is the X, Y, Z, XY, XZ, YZ directions. The second-order diffusion tensor ^[2] is a 3 * 3 matrix. By using a mathematical method called similarity transformation, the non-diagonal terms in the matrix can be eliminated. This is equivalent to resetting the Z-axis direction within the voxel so that it is located in the main direction of the white matter tract. This direction is called the principal eigenvector. The dispersion coefficient in this direction is called the principal eigenvalue. In addition to the principal eigenvector and the eigenvalue, the new eigenvector is described in a direction perpendicular to the new Z axis (new X and Y axis).

Diffuse tensor imaging data parameters

Mean diffusion rate

(1) Mean diffusivity MD. In order to comprehensively evaluate the diffusion status of a certain voxel or region of the tissue, the effect of anisotropic diffusion must be eliminated and expressed using a constant parameter, that is, It is said that the change of this parameter does not depend on the direction of dispersion. Among several elements of the diffusion tensor, the trace of the diffusion tensor is a constant parameter, Tr (D) = DXX + DYY + DZZ, and the average diffusion rate MD = 1/3 Tr (D ) = 1/3 (DXX + DYY + DZZ). MD reflects the overall dispersion level of the molecule (the size of the average ellipsoid) and the overall situation of the dispersion resistance. MD only indicates the size of the diffusion, and has nothing to do with the direction of the diffusion. The larger the MD, the more free water molecules are contained in the tissue.

Degree of anisotropy for diffusion tensor imaging

Diffusion tensor imaging pictures (7 photos)

(2) The degree of anisotropy, which reflects the degree of molecular displacement in space, is related to the direction of the tissue. There are many parameters for quantitative analysis of anisotropy, such as anisotropic fraction (fractional anisotropy, FA), relative anisotropy (RA), volume ratio index (VR), and so on. These indices are calculated from the eigenvalues of the diffusion tensor (ie, 1, 2, and 3).

FA; part of the anisotropy index is the proportion of the anisotropic component of the water molecule to the entire diffusion tensor, which ranges from 0 to 1. 0 means that the diffusion is not limited, such as the FA value of the cerebrospinal fluid is close to 0; for very For regular directional tissues, the FA value is greater than 0. For example, the FA value of white matter fibers in the brain is close to 1.

The formula for calculating the FA value is as follows:

FA = 3 [(1- <>) 2 + (2- <>) 2 + (3- <>) 2] / 2 (12 + 22 + 32)

= (1 + 2 + 3) / 3

RA: Relative anisotropy index is the ratio of the anisotropic part of the diffusion tensor to the isotropic part of the diffusion tensor. It varies from 0 (isotropic dispersion) to 2 (infinity anisotropy). .

The formula for calculating RA is:

RA = (1- <>) 2 + (2- <>) 2 + (3- <>) 2 / 3 <>

VR: Volume ratio index. Is the ratio of the volume of the ellipsoid to the sphere. Because it varies from 1 (ie, isotropic dispersion) to 0, it is clinically more inclined to apply 1 / VR.

The calculation formula of VR is as follows:

VR = 1 × 2 × 3 / <> 3

The main direction of diffusion tensor imaging

(3) The main direction of diffusivities, that is, the principal axis of the ellipsoid of the diffusion tensor, reflects the spatial direction of the organizational structure.

Although there are many parameters that reflect anisotropy, by 2015 clinically, FA values are more commonly used. The reasons are as follows: First, because FA images can provide better gray and white matter contrast, it is easy to select regions of interest. Makes the measured FA value more accurate; second, the FA value does not change with the change of the coordinate system rotation direction, and the FA value is a physical property of the tissue. The values obtained at different times on the same object, between different imaging equipment, and between different objects have Comparability.

Diffuse tensor imaging data acquisition

DTI Common DTI acquisition techniques for diffusion tensor imaging

Single-excitation echo planar imaging (EPI) technology. A single shot yields all raw data in K-space. The imaging time of this method is significantly shorter than that of general physiological movements (such as: breathing, heartbeat, etc.), which greatly reduces motion artifacts. However, the spatial resolution and signal-to-noise ratio of the single-shot EPI are both low, and the deformation caused by magnetic sensitivity is more obvious. To this end, Bammer et al. A single-shot EPI method of sensitivity-trinity encoding (SENSE) is proposed. In the same scanning time as the conventional EPI, the spatial resolution of the image is significantly improved, and the geometric distortion is significantly reduced. Yamada et al. Also reported that a single shot of EPI using parallel imaging technology can achieve similar results.

Multiple excitations of EPI have higher spatial resolution and signal-to-noise ratio and less distortion due to magnetic sensitivity than single-shot techniques. However, the long acquisition time is more sensitive to artifacts caused by breathing, cerebrovascular and cerebrospinal fluid flow, eye movements and involuntary head movements, which are its main disadvantages. Since the technique does not continuously fill the K space after multiple excitations, even slight body movements of the examinee can cause artifacts. It can only be controlled by ECG gating or navigation echo technology.

DTI Factors Affecting DTI in Diffusion Tensor Imaging

DTI is affected by the intensity and direction of the dispersion-sensitive gradient field, and the intensity of the dispersion-sensitive gradient field can be optimized by setting different b values. Generally, the b value applied is between 0 and 1000 s / mm2. Jones and others believe that optimizing the number of sensitive gradient spatial directions and increasing the number of them can reduce noise and improve the accuracy of tracking nerve fiber bundles. However, Hasan et al. Found through simulation analysis that as long as the gradient direction is optimized, there is no significant benefit from using more than 6 encoding directions.

DTI DTI data correction for diffusion tensor imaging

The misregistration of DTI adversely affects the spatial resolution of the image and the accuracy of the anisotropy calculation. The geometric distortion of the image and the slight movement of the examinee are the main causes of poor DTI registration. The former is mainly caused by poor shimming, differences in the magnetic properties of adjacent tissues, and non-uniformity of the static magnetic field caused by eddy currents. The use of an unwarping algorithm can correct the geometric deformation of the image. Applying automatic image registration software (AIRS) can correct the misregistration caused by motion.

Noise is also one of the factors affecting the tracking effect of nerve fiber bundles, which is mainly solved by regularization mathematical processing. Because the relevant knowledge is very limited, so far, regular processing has been performed based on the assumption of the limited curvature of the fiber bundle.

Diffusion tensor imaging tracking technology

DTT Basic principles of DTT imaging for diffusion tensor imaging

Previous research on white matter fiber (WMF) in the brain mainly relied on the brain tissue or autopsy of living animals. Although conventional magnetic resonance imaging such as T2WI, FLAIR, and MT (magnetization transfer imaging) images can show the difference between white matter and gray matter in the brain, these imaging methods cannot show the direction of the white matter fibers in the brain, so they cannot provide complete white matter. Anatomy of the fiber. DTI reflects the direction-dependent characteristics of water molecule dispersion in WMF. Its FA image can show the structure and anisotropic characteristics of white matter fibers in the brain, such as the inner capsule, corpus callosum, and outer capsule. But DTI cannot provide how white matter fibers are connected between adjacent voxels. With the continuous development and use of computer software, people use the data obtained by DTI to perform brain white matter fiber imaging. This is diffusion tensor tractography (DTT). DTT is a further development of DTI technology. Identify special fiber channels in the brain and their connections. Since DTT is a newly applied magnetic resonance diffusion imaging technology, its name is still not uniform, for example, it is called fiber tracking technology or white matter fiber bundle imaging (tractography).

Although there are many calculation methods, the general principle is to connect voxels containing the same axon. By 2015, 3D white matter fiber bundle imaging can be roughly divided into two methods: one is line propagation techniques, which uses local tensor information as a step of expansion; the other is the energy minimization method ( energy minimization techniques), which uses the smallest amount of energy to find the best channel between two pre-set pixels, and can be divided into two types, fast marching technique (FMT) and simulated annealing ( simulated annealing approach (SAA).

The basic principle of DTT imaging is to assume that the maximum eigenvalue 1 in diffusion tensor imaging represents the direction of the locally dominant fiber axon. Mori et al. First performed experiments on animals in 1999 and successfully showed the 3D structure of white matter fibers in the brain.

Limitations of diffusion tensor imaging fiber tracking technology

There is no gold standard for tracking living fibers. In fact, DTI is the only way to show the trajectories of nerve fiber bundles in vivo. Because tissue specimens undergo anatomical, freezing, dehydration, fixation, sectioning, and dissolving processes, their microstructures will inevitably change, resulting in geometric deformation. It is very difficult to verify the results of living body tracking in vitro using histological methods. At the same time, diffusion-weighted imaging due to poor registration caused by eddy currents, artifacts caused by motion of the examinee, and signal loss due to magnetic sensitivity can all affect the calculation results and produce adverse effects. Although many of these issues have been improved, there are still significant limitations.

Partial volume effect is also an important factor affecting the reliability of tracking results. Since the diffusion tensor used for fiber tracking is a voxel average. In anisotropic tissues with the same fiber direction, the maximum eigenvector can be used to accurately estimate the micro fiber direction. However, when the fiber distribution direction is not the same, the MR signal we measure depends on the structure of the tissue in a complicated way. The maximum eigenvector is only consistent with the average fiber direction within the voxel. If the voxel contains curved fiber bundles, it can be improved by reducing the voxel. If the voxel contains two or more components, such as different fiber components interlaced in canine teeth, the problem cannot be solved by reducing the voxel. When different fiber bundles cross, fit, branch, or fuse within the same voxel, the fiber bundle trajectories calculated according to the tensor domain will not reflect the true trajectories of the fiber bundles. This problem can be partially solved by using high angular resolution and high b-valued dispersion gradient sampling schemes.

Noise can also adversely affect fiber tracking. First, it can cause erroneous classification of eigenvectors, which can cause the calculated trajectory to suddenly deviate by 90 degrees, causing the trajectory to jump to another fiber bundle. Even when the eigenvector is correctly classified, noise in the data can cause the eigenvector distribution to diverge, causing the tracking results to deviate from the true trajectory. Moreover, due to the influence of noise, even MRI data obtained under the same conditions cannot produce exactly the same trajectory.

Clinical application of diffusion tensor imaging

(cerebral ischemia) Cerebral ischemia with diffusion tensor imaging

When the cerebral blood flow drops below 10-15 ml / 100 g / min, the intracellular water volume will increase, and water will flow into the cells from the interstitial space, causing the cells to swell, resulting in cytotoxic edema. With traditional MR, acute cerebral infarction is difficult to detect, and the extent of ischemic brain parenchyma can only be detected at a later stage when vasogenic edema appears. When normal MR manifestations are normal, DWI and DTI can detect acute cerebral infarction early. They make it possible to identify changes in the acute and chronic phases of cerebral infarction, which have important clinical value for the choice of treatment methods. In the acute phase, within 30 minutes of the onset of focal cerebral infarction, the ADC value initially decreased by about 30-50%. In the acute and subacute early stages, the ADC of white matter in the infarct area decreased more significantly than that of gray matter. For ischemic cerebral infarction, DTI parameters such as MD initially decrease, then increase, and finally higher than normal. During the chronic phase of the injury, ADC has remained elevated. In the interval period when the ADC first decreases and then rises, there is a period when the ADC value behaves normally. This period is called the "false normal period". In adults, this period is about 9 days after cerebral infarction, and about 7 days in newborns. In addition to the changes in ADC, there is an acute increase in the FA value of the white matter in the infarct at the early stage of ischemia. After this acute increase, the FA value will decrease significantly in the chronic phase. This change is thought to be due to the loss of the normal structure of the tissue microstructure due to the destruction of the cell structure.

In the chronic phase of cerebral infarction, relative to the renormalization of ADC and subsequent elevation, the FA value of the diffuse anisotropy index is significantly lower than that of normal brain tissue in the same region on the contralateral side, even in ischemic cerebral infarction 2-6 After one month, the FA value of the infarct was still lower than the healthy side. ADC threshold may have important value in predicting tissue survival and prognosis of ischemic cerebral infarction. The combination of ADC and anisotropic parameters can well define the clinical stage of ischemic cerebral infarction.

In some cases, early in the ischemic cerebral infarction, ADC appears to increase rather than decrease. Usually, ADC decreases immediately after the appearance of cytotoxic edema, but ADC can also increase early when vasogenic edema occurs simultaneously. For example, in reversible posterior leukoencephalopathy syndrome, or hypertensive hydrocephalus.

leukoariaosis Diffuse tensor imaging of leukoariaosis

Leukopenia has non-specific imaging findings, and diffuse changes of the white matter around the ventricle can be seen on CT or MR. It can occur in a variety of white matter diseases including chronic cerebral ischemia, Alzheimer's disease, autosomal dominant cerebral arterial disease with subcortical infarction and white matter encephalopathy. In histological manifestations, axonal loss and glial proliferation can be seen. In ischemic leukoencephalopathy, T2 weighted images show areas of increased signal, and DTI shows increased mean diffusion coefficient MD and decreased FA value. The mean diffusion coefficient of leukoencephalopathy is significantly lower than that of lacunar cerebral infarction lesions, presumably due to the former's glial growth preventing the diffusion of water molecules.

3. Wallerian degeneration (WD)

Wallerian degeneration is the anterograde degeneration of axons, and myelin disintegration of neural axons is secondary to adjacent axonal injury or nerve cell death. The most common is cerebral infarction secondary to ipsilateral, with WD appearing in the corticospinal tract. In WD, DTI is more sensitive than T2WI images. Diffusion anisotropy index such as FA value decreases in both the primary lesion and the area where WD occurs. However, ADC values were only slightly increased in WD and significantly increased in primary ischemic infarction. In this way, the primary lesion and WD can be distinguished by the ADC value.

Diffusion tensor imaging of brain development, maturation and degeneration

(developing brain, maturation and aging)

DTI has many challenges in studying brain development. Some studies have shown that in the brain tissue, using the same pulse sequence and post-processing method for DTI examination of children and adults (except for different b-values, 1000 mm2 / s for adults and 700-800 mm2 / s for children), brain tissue can be found. The ADC value and diffusion anisotropy index change regularly with age. The neonatal brain tissue ADC value is significantly higher than that of adults, and the FA value is significantly lower than adults. In children, ADC values for white matter are significantly higher than gray matter. The ADC in the center of the semi-oval is close to 2.0 × 10-3mm2 / s. As the age increases, the ADC value decreases until it reaches 0.7 × 10-3mm2 / s for adults, and the anisotropy index increases (especially during the development of RA , Rising in a non-linear way). The change of ADC value mainly occurred in the first 6 months of the baby's birth. This change was considered to be related to the decrease of brain tissue water volume, the formation of axonal myelin sheath, and the formation of white matter fiber structure. These factors all reduced the average diffusion rate. This phenomenon can be found in different regions of the brain, and the ADC value changes with age.

DTI has been used to study the physiological degradation of brain tissue with the goal of discovering age-related changes. Adults over 40 years of age have higher ADC values for white matter than young people. In addition, after 20 years of age, the degree of diffuse anisotropy will decline. In the deep white matter with dense white matter fiber bundles, the FA value of the white matter will show an age-related downward trend, especially the corpus callosum and semi-oval center. These age-related physiological changes should be considered when assessing the impact of the disease, especially in the elderly.

Diffuse tensor imaging diffuse axonal injury

(diffuse axonal injury, DAI)

With the exception of cerebral infarction, most focal brain injuries have not been extensively studied using DTI. Traumatic brain injury is divided into focal and diffuse. Focal brain injury is often caused by a direct external force, such as a hematoma or a cerebral contusion. Diffuse brain injury is often the result of shear injury, or a drag injury caused by deceleration in different parts of the brain tissue due to different densities and stiffnesses. DWI can be used to check for non-obvious shear injuries on conventional MR images. However, DWI is less sensitive than T2WI in the display of bleeding lesions. There will also be a semi-dark area around focal lesions such as brain contusions or hematomas, where the diffusion coefficient will decrease. The presence of this penumbra may be important in the choice of treatment plan for patients with head trauma.

Most of the histopathological abnormalities in the inner capsule and corpus callosum show changes in the degree of diffuse anisotropy. In the first 24 hours after traumatic diffuse axonal injury, white matter that appears normal on normal MR may show a slight decrease in diffuse anisotropy index. After a few weeks of trauma, this decline will be obvious. In the perinatal period, newborns with high-risk brain injury can show a decline in ADC values on the first day after birth when the brain parenchyma is normal on T1WI or FLAIR. However, a significant drop in ADC values occurred on day 3. At the same time, the ADC value can be falsely normalized within one week. Therefore, DTI can not fully display the range of neonatal trauma on the first day after trauma. The image on the third day after trauma may better show the range of trauma. In the near future, there will be further research to evaluate the value of DTI for measuring the extent and prognosis of parenchymal injury, and to find the best DTI examination time.

Prospects for diffusion tensor imaging

DTI technology is a non-invasive and powerful tool for studying the complex brain tissue structure. It has broad application prospects in neuroanatomy, fibrous connection, and development of the brain ^[7] . It has huge potential advantages for research on neurological diseases ^[8] and brain function ^[9] . Although the measurement of DTI parameters and its images will not be a reliable standard for clinical diagnosis by 2015, the examination of certain organs is subject to objective conditions. With the improvement of technology and better post-processing analysis, DTI will be more extensive, More reliable applications in research and clinical work ^[10] .