Principles of diffusion imaging
Diffusion imaging focuses on the micromovements (random, brownian) of
the water molecules inside voxels. These motions encounter different
obstacles in the body (cell membranes, proteins, macromolecules,
fibers…), which vary according to the tissues and certain pathological
modifications (intracellular edema, abscess, tumors…).
Essentially, extracellular water is the main object of exploration in diffusion imaging. Diffusion data provides indirect information about the structure surrounding these water molecules.
Stated simply, the displacement of water molecules can be summarized into three different types of freedom of movement.
the water molecules displace freely in all spatial directions. A
typical example of this corresponds to fluids such as cerebrospinal
fluid.
water molecule displacement is restricted, in whatever spatial direction, by numerous obstacles (proteins, cells)
Example: abscess, tumor at high cell density
Certain structured tissues create obstacles that orientate the motion of
the water molecules (tendency to displace themselves in one or several
particular directions). Diffusion is only restricted in certain spatial
directions.
Example: nerve fibers (organization in bundles of axons running in parallel, with concentric layers of myelin restricting transversal diffusion)
DW-MRI aims at highlighting the differences in water molecule mobility, irrespective of their direction of displacement.
Diffusion tensor MRI, on the other hand, studies the directions of water molecule motion to determine, for example, whether or not they diffuse in all directions (fractional anisotropy), or attempts to render the direction of a particular diffusion (which can be applied to indirectly reconstituting the nerve fiber trajectory).
The diffusion gradients are strong and symmetrical in relation to the 180° rephasing pulse:
Taking the entire population of water molecules in a voxel, the faster
the water molecules diffuse, the more dephased they will be and the
weaker the recorded signal.
This technique allows diffusion weighting of any imaging sequence. The echo planar – spin echo sequence is generally preferred for its speed, which limits the (macroscopic) motion artifacts.
Parallel acquisition methods can be used to improve the quality of diffusion images by reducing sequence time, TE and certain artifacts.
In current practice, diffusion imaging of the brain consists of an acquisition with a b-factor b = 0 s/mm2 (T2-weighted) and imaging with a b-factor = 1000 s/mm2 (with diffusion weighting).
Diffusion sequences are actually T2 weighted sequences, sensitized to diffusion by gradients. The contrast of the diffusion image will have both a diffusion and a T2 component, which must be taken into consideration in the interpretation. Namely, a hypersignal in the diffusion image with b = 1000 s/mm2 can either correspond to a diffusion restriction or to a lesion that is already in T2 hypersignal (T2-shine-through).
with :
With:
The advantage of strong gradients is that they avoid the need to lengthen gradient time and spacing, which would impose an even longer TE (without removing the T2 weighting part of the signal).
If we have twin acquisitions with different b-factors, the ADC can be calculated.
Essentially, extracellular water is the main object of exploration in diffusion imaging. Diffusion data provides indirect information about the structure surrounding these water molecules.
Stated simply, the displacement of water molecules can be summarized into three different types of freedom of movement.
Free diffusion
Restricted isotropic diffusion
Example: abscess, tumor at high cell density
Restricted anisotropic diffusion
Example: nerve fibers (organization in bundles of axons running in parallel, with concentric layers of myelin restricting transversal diffusion)
DW-MRI aims at highlighting the differences in water molecule mobility, irrespective of their direction of displacement.
Diffusion tensor MRI, on the other hand, studies the directions of water molecule motion to determine, for example, whether or not they diffuse in all directions (fractional anisotropy), or attempts to render the direction of a particular diffusion (which can be applied to indirectly reconstituting the nerve fiber trajectory).
Diffusion-weighted sequences
Diffusion gradient
The aim of these diffusion-weighted sequences is to obtain images whose contrast is influenced by the differences in water molecule mobility. This is done by adding diffusion gradients during the preparatory phase of an imaging sequence, usually of the SE-EPI type (spin echo– ultrafast echo planar imaging preparation) that is T2 weighted.The diffusion gradients are strong and symmetrical in relation to the 180° rephasing pulse:
- the spins of the immobile water molecules between the applications of the two gradients are dephased by the first gradient and rephased by the second.
- the spins of the water molecules that move in the direction of the gradients, during the interval between the two gradient applications, will not be rephased by the second gradient: they dephase in relation to the hydrogen nuclei of the immobile water molecules.
This technique allows diffusion weighting of any imaging sequence. The echo planar – spin echo sequence is generally preferred for its speed, which limits the (macroscopic) motion artifacts.
Parallel acquisition methods can be used to improve the quality of diffusion images by reducing sequence time, TE and certain artifacts.
Diffusion weighting, ADC
The degree of diffusion weighting of the sequence, expressed as the b-factor (in s/mm2), depends on the characteristics of the diffusion gradients:- gradient amplitude
- application time
- time between the two gradients
In current practice, diffusion imaging of the brain consists of an acquisition with a b-factor b = 0 s/mm2 (T2-weighted) and imaging with a b-factor = 1000 s/mm2 (with diffusion weighting).
Diffusion sequences are actually T2 weighted sequences, sensitized to diffusion by gradients. The contrast of the diffusion image will have both a diffusion and a T2 component, which must be taken into consideration in the interpretation. Namely, a hypersignal in the diffusion image with b = 1000 s/mm2 can either correspond to a diffusion restriction or to a lesion that is already in T2 hypersignal (T2-shine-through).
Diffusion gradients and b-factor
b-factor is determined by the following relationship:with :
With:
- G = gradient amplitude
- t = gradient application time
- Δ = interval between the centers of the two diffusion gradients
The advantage of strong gradients is that they avoid the need to lengthen gradient time and spacing, which would impose an even longer TE (without removing the T2 weighting part of the signal).
Calculating the apparent diffusion coefficient (ADC)
The relationship between b-factor and diffusion signal weighting is of the type:If we have twin acquisitions with different b-factors, the ADC can be calculated.
T2-weighted and Diffusion-weighted signal
T2-weighted and Diffusion-weighted signal
|
Diffusion-weighted image (b1000) (Diffusion + T2) | T2 -weigthed signal (B0) | ADC (Diffusion alone) | |
| Restricted diffusion | hyper | iso | hypo |
| hyper ++ | hyper | hypo | |
| T2-shine-through | hyper | hyper | iso |
| Accelerated diffusion | hypo | iso | hyper |
| iso | hyper | hyper | |
| T2-dark-through | hypo | hypo | iso |
Diffusion tensor and anisotropy
The microarchitecture specific to nerve tissues causes diffusion
anisotropy in the white matter of the brain: water molecule diffusion
preferably follows the direction of the fibers and is restricted
perpendicularly to the fibers.
By performing diffusion-weighted acquisitions in at least 6 directions (and far more in angular high resolution imaging), it is possible to extract the diffusion tensor which synthesizes all the data.
The diffusion tensor characterizes diffusion: anisotropic
coefficient, preferred directions and restrictions in space. Different
images will be obtained depending on the complexity of the
post-processing of this data (figures 13.9 and 13.10):
By performing diffusion-weighted acquisitions in at least 6 directions (and far more in angular high resolution imaging), it is possible to extract the diffusion tensor which synthesizes all the data.
- Fractional anisotropy (null when diffusion is isotropic, of increasing value when diffusion becomes anisotropic)
- Main diffusion direction
- Fiber tracking
Local modeling of the diffusion phenomenon
The limitations of the tensor model in precisely determining the directions of water molecule displacements in the case of fiber crossing, for example, have led to the development of new models, which require a greater number of measurements:- Multitensor model (several diffusion tensors coexisting in a voxel)
- Q-ball (S-space): requires a large number of acquisitions in different directions, with a constant b-factor
- Q-space (Diffusion spectrum imaging) (figure 13.11): the ultimate technique, able to describe fiber crossings, but requiring a high number of acquisitions (129 to 515 !) in different directions and with different b-factors to sample the diffusion equivalent of a 3D k-space
Artifacts and image quality in diffusion imaging
The artifacts basically stem from the use of
Diffusion-weighted sequences are highly sensitive to macroscopic motions (patient, vascular pulsations…). By virtue of their speed, echo planar sequences will avoid such artifacts. If other, slower types of sequence are used, it may be necessary to synchronize acquisitions with the ECG or with an echonavigator.
In diffusion tensor imaging, the main limitation concerns the fiber crossings in the same voxel: the main diffusion direction given by the diffusion tensor does not correspond to a real trajectory and this can lead to errors in a nerve fiber tractography algorithm. The other problem in tractography refers to the fusions, divisions and angulations of the nerve fiber bundles. To overcome these problems, more diffusion measurements can be taken in different directions (HARDI: High Angular Resolution Diffusion Imaging) delivering more data to the algorithms, but at the cost of increased acquisition times.
- diffusion gradients that need to be strong: contraction / dilation and/or shift / distortion of the image (currents induced during gradient ascent and descent), image distortion (errors in gradient linearity), ghost images (gradient instability)
- fast imaging techniques (EPI): magnetic susceptibility effects, ghost images (induced currents).
Diffusion-weighted sequences are highly sensitive to macroscopic motions (patient, vascular pulsations…). By virtue of their speed, echo planar sequences will avoid such artifacts. If other, slower types of sequence are used, it may be necessary to synchronize acquisitions with the ECG or with an echonavigator.
In diffusion tensor imaging, the main limitation concerns the fiber crossings in the same voxel: the main diffusion direction given by the diffusion tensor does not correspond to a real trajectory and this can lead to errors in a nerve fiber tractography algorithm. The other problem in tractography refers to the fusions, divisions and angulations of the nerve fiber bundles. To overcome these problems, more diffusion measurements can be taken in different directions (HARDI: High Angular Resolution Diffusion Imaging) delivering more data to the algorithms, but at the cost of increased acquisition times.
Main applications of diffusion
At the present time, diffusion imaging is essentially
used for brain exploration in clinical practice. Nevertheless, new
applications are emerging outside neuroradiology (cancerology,
musculoskeletal radiology…).
Diffusion imaging was used in application to stroke. Indeed, diffusion imaging is the earliest and most sensitive method in diagnosing stroke (< 1 hour). It manifests in the acute phase as a drop in ADC translating an ischemic cytotoxic edema. It is also used to date the stroke event and to distinguish between acute and subacute strokes.
Diffusion imaging also participates in diagnosis in different categories of brain pathology:
Fiber tractography is the only method giving an indirect, in-vivo view of the nerve fiber trajectory (figure 13.12). It can be associated with functional MRI to study the interconnexions between nerve centers, used to analyze brain maturation and development (myelinization), assist in the preoperative check-up for brain tumors (corticospinal bundle) or for medullary compression. Diffusion tensor imaging can also be of interest in exploring Alzheimer’s disease, certain psychiatric affections, inflammatory, tumoral, vascular, traumatic (irreversible comas) pathologies or drug-resistant epilepsies.
Diffusion imaging (DW MRI)
Diffusion imaging was used in application to stroke. Indeed, diffusion imaging is the earliest and most sensitive method in diagnosing stroke (< 1 hour). It manifests in the acute phase as a drop in ADC translating an ischemic cytotoxic edema. It is also used to date the stroke event and to distinguish between acute and subacute strokes.
Diffusion imaging also participates in diagnosis in different categories of brain pathology:
- Tumoral: cerebral lymphoma (reduced ADC), epidermoid and cholesteatoma cysts (hypersignal in diffusion).
- Infectious: pyogenic brain abscess (reduced ADC, providing differential diagnosis from a necrotic tumor in which the ADC is increased), herpes encephalitis
- Degenerative: Creutzfeldt-Jakob’s disease (aid to early diagnosis)
- Inflammatory: MS
- Traumatic
Diffusion Tensor Imaging (DT-MRI)
Diffusion tensor imaging enables the in-vivo study of tissue microstructure. It gives indications about possible nerve fiber anomalies in white matter or the spinal cord that are not visible in conventional imaging.Fiber tractography is the only method giving an indirect, in-vivo view of the nerve fiber trajectory (figure 13.12). It can be associated with functional MRI to study the interconnexions between nerve centers, used to analyze brain maturation and development (myelinization), assist in the preoperative check-up for brain tumors (corticospinal bundle) or for medullary compression. Diffusion tensor imaging can also be of interest in exploring Alzheimer’s disease, certain psychiatric affections, inflammatory, tumoral, vascular, traumatic (irreversible comas) pathologies or drug-resistant epilepsies.
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