Diffusion-Weighted Imaging

106.1 Introduction

A drop of ink in a glass of water will spread through- out the water by a process known as diffusion. This phenomenon was first observed by Brown in 1827 and bears his name, brownian movement. His experi- ments, executed with Clarkia pollen spread on a wa- ter surface, led to wide speculations about the nature of the movements observed. “He suspended some of the pollen grains in water and examined them close- ly, only to see them ‘filled with particles’ that were

‘very evidently in motion’. He was soon satisfied that the movement ‘arose neither from currents in the flu- id, nor from its gradual evaporation, but belonged to the particle itself ’. In due course he was to carry out careful experiments to disprove these alternative ex- planations, and it has been shown that Brown was able to anticipate the later objections of those who would doubt his capacity to have observed what he claimed. It must have been tempting for Robert Brown to assume, as had other workers before him, that here was the very essence of life.” (Ford, 1992)

Much later it became clear that the movement of particles was the result of random movement of wa- ter molecules. Temperature proved to be an impor- tant factor in determining the rate of the movement of molecules, and therefore the process is also referred to as thermodynamic movement. The human body consists to 60–80% of water. Molecular movements in the body are modified by complex tissue compart- ments. The brain, for example, consists of many dif- ferent structures, restricting to a greater or lesser ex- tent the free movements of water molecules. This leads to differences in diffusion of water molecules between different brain structures, which makes dif- fusion a potential source of image contrast.When wa- ter movement is relatively unrestricted in all direc- tions, diffusion is isotropic; when restrictions are pre- sent in one or more directions, water movement is anisotropic. Diffusion in gray matter in adults is near- ly isotropic; on the other hand, diffusion in white matter, with its compact and organized structure of myelinated axons and fiber tracts, is anisotropic. Dis- ease states may also lead to changes in the freedom of water diffusion.

It has become possible, by using MR techniques with a spatial resolution in the order of square mil- limeters, to measure changes in the freedom of water

movement at the molecular level. MRI is based upon the resonance condition of protons brought about by a strong static magnetic field. Protons in this condi- tion can absorb and subsequently release energy of a special frequency (resonance frequency). The re- sponse or released energy of the protons can be col- lected by coils placed around the body or a body part as the MR signal. The MR signal is used to reconstruct images and depends on many factors, such as pulse sequence, slice thickness, matrix, and number of ac- quisitions. The strength of the signal is ultimately the sum of protons in and out of phase in a pixel (picture element) or, more correctly, in a voxel (volume ele- ment). With all other parameters identical, the signal is at its maximum when all protons in a voxel are in phase. The signal decreases when a number of pro- tons are out of phase (or dephased). Diffusion of wa- ter molecules leads to dephasing of protons and therefore loss of signal. This means that in MR images unrestricted diffusion leads to loss of signal and re- stricted diffusion leads to a smaller loss of signal. On a relative scale this means that tissue with restricted diffusion will appear brighter in the image, while tis- sues with less restricted diffusion will appear darker.

The contribution to dephasing of protons caused by diffusion of water molecules in the order of cell dimensions, 5–25 mm

/s, is not detectable on images made with standard MR pulse sequences. Two devel- opments were necessary to realize the visualization of diffusion effects with MR equipment. The first was the improvement of the temporal resolution by ultra- fast imaging techniques (now usually single shot echo planar pulse sequences). These techniques have the advantage of “freezing” motion. Motion in the order of cell dimensions is rapidly overshadowed by move- ments of the patient, voluntary and involuntary, by respiration, and pulsation of vessels and cere- brospinal fluid. The second requirement was the introduction of a set of strong, opposed “diffusion”

gradients enhancing the diffusion process. Applica- tion of these techniques has made it possible to intro- duce diffusion-weighted imaging (DWI) into clinical practice. The MR application of DWI is practiced on two levels: a relatively simple level with rapid acquisi- tion of clinically useful information, and a more complex level allowing more precise estimation and quantization of anisotropy and 3D analysis of the data.

Diffusion-Weighted Imaging

Chapter 106

106.2 DWI Techniques

For DWI it is necessary to use ultrafast sequences to “freeze” motion, as mentioned above. Even then, however, the small contribution of diffusion to the dephasing of protons is not visible on single shot echo planar images and is easily overshadowed by T

effects. It is necessary to enhance the diffusion effects by applying strong, opposed diffusion gradients (Stejskal–Tanner sequence) (Stejskal and Tanner 1965; Fig. 106.1) that cancel all “coherent” motion within the voxel and enhance the effect of diffusion of protons.

The diffusion sensitivity is expressed as the b value of the sequence and usually varies between 500 and 4000 s/mm

. On commercial scanners the maxi- mum value often does not exceed 2000; usually b = 1000 s/mm

. Quantitative information about dif- fusion can be obtained in several ways. The simplest way is to measure the apparent diffusion coefficient (ADC) of the tissue. There is an exponential decrease in signal intensity with increasing b values. The ADC is measured by estimating the slope of the exponen- tial curve describing the signal intensities at different b values. Measurements at two or more different b values (usually 500 and 1000) are used to calculate the ADC. The word “apparent” refers to the fact that in vivo it is not possible to measure the “pure” diffusion coefficient D. The diffusion coefficient measured – the apparent diffusion coefficient – averages different tissues with different diffusion coefficients present in one voxel; it is also influenced by other parameters, such as the presence of microparticles of iron. ADCs

describe the effective averaged diffusion per voxel.

The diffusion coefficient in free water at 25 °C is about 25 ¥ 10

mm

/s. In brain tissue ADC values are in the order of 0.70–0.90 ¥ 10

mm

/s. In acute lesions, such as in acute ischemia, the ADC values decrease by about 50% to reach values of 0.40–0.60 ¥ 10

mm

/s.

In chronic ischemic lesions, with liquefaction and necrosis, these values may go up to 1.80–2.40 ¥ 10

mm

/s.

In routine DWI, diffusion gradients are applied in three orthogonal directions. Images can be obtained on the basis of the results of each gradient separately, in respectively the slice (s), read (r), and phase (p) direction (Fig. 106.2). Where fiber tracts are parallel

Fig. 106.1. Stejskal–Tanner pulse sequence, in which G is the diffusion gradient strength, D the distance between diffusion gradients, and d the duration of the diffusion gradient. The diffusion sensitivity (gradient moment or b value) of this se- quence increases when (1) the gradient strength (G) increases, (2) the duration of the gradient (d) is longer), and (3) the time between the opposed gradients (D) is longer. These relations are brought together in the following equation: b = g²G²d² (D–d/3), in which g is the gyromagnetic ratio

Fig. 106.2. Diffusion-weighted images in a patient with a right-sided homonymous hemianopia, made with three differ- ent diffusion gradients in x (read), y (phase), and z (slice) direc- tions, showing anisotropy dependent on the direction of the

diffusion gradient. Tracts perpendicular to the gradient show high signal intensity, tracts parallel to the gradient show lower signal intensity. Note that the small lesion in the left occipital pole demonstrates restricted diffusion in all three directions

with the direction of the applied gradient, signal loss due to diffusion will be at its maximum; where fiber tracts are perpendicular to the gradient direction, sig- nal loss due to diffusion will be at its minimum and the signal will remain relatively high. The opposite is true for ADC maps: the greater the restriction in dif- fusion, the lower the ADC value, and the lower the sig- nal intensity of that area. There is an important disad- vantage to using images with the application of only one diffusion gradient in one direction. Fiber tracts perpendicular to the gradient direction have a rela- tively high signal, which may obscure hyperintense lesions with restricted diffusion in or in the neighbor- hood of these structures or simulate a hyperintense lesion. This pitfall can be omitted by averaging the ADC values of the measurements with (at least) three diffusion gradient directions (Fig. 106.3).

Diffusion is a process in time. That means that the MR sequence has to cover a minimum time slot to ob- serve the diffusion process. Therefore, a relatively long echo time has to be applied, resulting in a T

- weighted EPI sequence. This leads to a high signal in- tensity of structures with a long T

. This high signal area may retain its brightness on diffusion-weighted images, simulating restricted diffusion. This phe- nomenon is referred to as “T

shine-through” effect.

ADC maps do not share this problem. It is therefore

extremely important for the demonstration of re- stricted diffusion to look at the ADC values and veri- fy the presence of a decreased ADC (Fig. 106.4).

Diffusion can be viewed as the product of the de- grees of freedom of movement of water in three di- mensions (x, y, and z). With equal movement oppor- tunity in all directions (isotropy), the product is a rounded sphere and the diffusion vectors are equally long. Where diffusion is anisotropic, the product is an ellipsoid, the vectors unequal in different directions.

The main vector, its size and direction can be estimat- ed. With gradients applied in three directions, the D value can be estimated voxel by voxel by averaging the D values obtained in three (or more) different gradi- ent directions: D = (Dxx + Dyy + Dzz) / 3. This aver- aging procedure will also cancel anisotropy in the image. The resulting image is called a Trace image (Figs. 106.3 and 106.5).

Diffusion Tensor Imaging In isotropic substances, diffusion can be described by a single parameter, the diffusion coefficient, or rather, the apparent diffusion coefficient, ADC. The attenuation of the MR signal depends on D and the b value, characterizing the gra- dient pulse:

A = exp(–bD)

106.2 DWI Techniques 841 Fig. 106.3. The images on the left are

made with a single diffusion gradient.

In the left upper image one sees, in addition to the bright spot in the thalamus, high signal intensity in fiber tracts perpendicular to the gradient direction. The lower left image shows anisotropy of the splenium of the corpus callosum with a gradient in the slice direction. The images on the right are Trace diffusion-weighted images, which average diffusivity of three (or more) gradient settings to mini- mize the influence of anisotropy in the image. The upper right image now shows only the lesion in the right thalamus. The lower right image does not show any areas of restricted diffusion

Fig. 106.4. The next series shows the application of DWI techniques in a clinical situation, the effect of different b values of the diffusion gradients and the added value of ADC maps. The upper row represents the conventional T2-weighted image and T1-weighted images without and with contrast. The lesion in the right middle cerebral artery territory is visible. The middle row shows Trace diffusion-weighted images with different b value settings; from left to right: b = 50 s/mm², 500 s/mm², 1000 s/mm². With higher b values more and more structural information gets lost in the image, whereas the information about the abnormal area increases. The Trace diffusion-weighted images must be checked against the corresponding ADC maps (lower row). The combination of high signal intensity on Trace diffusion- weighted images and low ADC values (<50 %) argues for the presence of cytotoxic edema or other causes of restricted diffusion

Fig. 106.5. The image on the left was obtained with a single gradient in the slice direction. In the Trace diffusion-weighted image on the right the effect of anisotropy in the splenium of the corpus callosum, as seen on the left, has disappeared

in which A is attenuation, b is diffusion sensitivity, and D is the diffusion coefficient. With anisotropy present, a single parameter is no longer sufficient.

With the mathematical description of the diffusion tensor, effects can be fully extracted, characterized, and exploited. The tensor D

is necessary to describe the molecular movements in each possible direction.

In this model isotropic diffusion can be depicted as a rounded sphere, anisotropic diffusion as an ellipsoid tilted in the direction of the main orientation of the diffusion (Fig. 106.6).

The anisotropic diffusion process in each voxel can be characterized by D

, consisting of a 3 ¥ 3 tensor matrix consisting of nine combinations, of which three are similar and six are independent. By sam- pling signal attenuation after applying diffusion-sen- sitizing gradients in at least six different noncollinear directions, these six (or more) elements can be deter- mined. They represent diffusion along the three main coordinate axes of the ellipsoid, thus defining the shape of the ellipsoid (Fig. 106.7).

The data so obtained are rotationally independent:

the head can be placed in an arbitrary position in the main magnet and this will not influence the results.

The data can be used to calculate either the “diffusiv- ity”, <D> (the directionally averaged ADC), or the de- gree of anisotropy, most often expressed as relative anisotropy (RA), or as fractional anisotropy (FA). In 2D representations of diffusion tensor imaging (DTI), FA is the most frequently used of many possible para- meters describing anisotropy. RA is the ratio of vari- ance of the eigenvalues to their mean. FA is the ratio of the anisotropic component of the diffusion tensor over the whole diffusion tensor. FA indicates how elongated the ellipsoid is (0 = isotropy, 1 = maximum anisotropy, often multiplied by 1000). FA is usually displayed as a map in gray shades (higher FA values reflecting more pronounced anisotropy show a high- er signal intensity on gray scale images, low values appear darker) (Fig. 106.8) or in color codes. FA im- ages show more contrast between gray and white matter than do T

- and T

-weighted images. The rea- son for this difference is still not fully clear, but may have to do with the major difference in density of axon fibers. In the literature ratios are used to quanti- tate FA values, because values are not the same on all systems. The ratio is calculated as:

106.2 DWI Techniques 843

Fig. 106.6. Diffusion tensor (matrix). In isotropic conditions Dxx, Dyy, and Dzz suffice to determine the diffusion vectors. In anisotropic conditions Dxy, Dxz, and Dyz are also important to define the strength and directions of vectors in a voxel

Fig. 106.7. Ellipsoid representing the diffusion tensor. The ellipsoid is characterized by the maximum diffusion in each direction and represents the relationship between the princi- pal coordinate axes (x’, y’, and z’) and the laboratory reference frame (x, y, z). The radii (bold black arrows) represent the mag- nitude and direction of the diffusion after unit time. The l1, l2, and l3represent the so-called eigenvalues of diffusivity in all directions, shaping the ellipsoid

Fig. 106.8. A fractional anisotropy (FA) map provides a mea- sure of anisotropy of different structures. Differences in FA between gray and white matter structures are greater than differences in T1, T2, or ADC values. In a FA map the distinction between gray and white matter structures is superb

rFa = FA lesion

× 100 % FA reference point

or, somewhat more complex:

∆FA = FA patients – (FA controls)

× 100 % (FA controls)

in which equation “(FA controls)” stands for the mean value from the regions of interest in volunteers. In particular in multicenter studies and trials ratios will have to be used to overcome inequalities in equip- ment performance.

A map can also be produced displaying the princi- pal vector orientation per voxel. This is most often displayed as a color map in which the vectors (small arrows) are presented in color codes per direction.

DTI may be used to create a 3D map by connecting adjacent vectors with nearly the same orientation.

Software programs usually allow the setting of a threshold that indicates the degree of accepted anisotropy (FA value), and also the setting of an arbi- trary angle to decide whether a fiber connection will be accepted. The result is fiber tracking: white matter tracts can be visualized (Fig. 106.9). DTI cannot dis-

tinguish afferent from efferent tracts; the spatial res- olution within acceptable acquisition times is still crude; and crossing fibers may lead to confusing results. Nevertheless, the potential of the method is, especially in combination with other techniques such as functional MRI, impressive.

106.3 DWI and Pathophysiological Backgrounds

DWI, usually in its simplest form with three diffusion gradients, anisotropy images, Trace images, and ADC maps, is now widely used in clinical practice. It has become a valuable tool in the detection and diagnosis of a growing number of neurological disorders. The pathophysiological background of the changes in the acute phase of diseases and the changes over time into subacute and chronic conditions are only partly understood. Diffusion is a parameter that is indepen- dent of the relaxation properties (T

and T

) of tissue.

Brain tissue consists of cell structures, with mem- branes dividing tissue fluid into extracellular and in- tracellular compartments, organelle compartments,

Fig. 106.9. Diffusion tensor imaging allows fiber tracking as is demonstrat- ed in this image. DTI was done with 12 diffusion gradient directions. Fibers were tracked connecting left and right hemisphere via the corpus callosum, showing the potential of the method.

The upper image shows a comparable anatomical specimen

blood compartments consisting of arterioles, venules, and capillaries sustaining the microcirculation, and fiber tract compartments with myelin and axons, all having their impact on the complex process of diffu- sion.

The best understood changes are those in acute ischemic lesions (Fig. 106.10). Hypoxemia and is- chemia lead to membrane depolarization, changes in membrane permeability, changes in ion exchange, and influx of water into the cell. Swelling of cells, both

106.3 DWI and Pathophysiological Backgrounds 845

Fig. 106.10. DWI and ADC maps, often in combination with perfusion imaging, play an important role in stroke units, to identify salvageable tissue. This set of images shows such a practical application in a 66-year-old stroke patient. The upper row of FLAIR images shows lesions in the right middle cerebral artery territory. The second row of DWI–Trace images shows

bright signal in these lesions. The lower row of ADC images shows very low ADC values in the lesions, confirming the pres- ence of cytotoxic edema.The added value to the FLAIR images is the time dependency of the DWI–ADC techniques, allowing an estimate of the age of the infarction

glia and neurons, lead to compression of the extracel- lular space and restriction of movement of extracellu- lar water, and probably also to restriction of intracel- lular water movements due to changes in organelles.

This results in a high signal on DWI–Trace images and low ADC values. Subsequent lysis and shrinking of cells and rarefaction of tissue leads to increase of extracellular space and water content, with conse- quently a decrease of signal intensity on Trace images and increase of ADC values. The time frame for these changes in arterial territorial infarctions is in the or- der of 2–4 weeks. It should be noted that this time frame is different in border zone infarctions, where high signal on Trace images and low ADC values per- sist for much longer, even months. This is the result of a more chronic and persistent perfusion deficit.

In acute encephalitis and cerebritis, for example, in herpes simplex encephalitis,ADC values can be as low as in ischemic lesions. In viral infections there is swelling of cells and decrease of extracellular space in the initial phase, comparable to what happens in is- chemia. It remains to be seen whether ADC and FA provide a means of estimating prognosis or of esti- mating disease activity in subacute lesions or recur- rent infection.

Many other factors may influence the degree of freedom of movement of water molecules in brain tis- sue. High cellular density and high nucleus/cyto- plasm ratio of packed cells in tumors may cause low ADC values. In brain abscesses, the restriction of wa- ter movement is based upon cellular density, forma- tion of septa, and gelatinous or caseous contents of the abscess cyst (Fig. 106.11). Epidermoids also show restricted diffusion, caused by the gelatinous condi- tion of the fluid and the presence of septa.

In focal epilepsy there is a reduction of 20% of ADC values of the tissue involved in the ictal phase, while MRA, MR perfusion studies, and SPECT show evidence of hyperperfusion in that area. In the inter- ictal phase, the ADC values return to normal in days to weeks. In addition to swelling of involved neurons, the increase in regional blood volume may influence the measurements by an increase of magnetically ac- tive blood products, for example deoxyhemoglobin.

Blood present in post-traumatic or postoperative cysts may lead to a pseudo-low ADC and in that way suggest an abscess. T

-weighted images usually will solve this problem, when it arises.

In white matter disorders, inherited or acquired, multiple factors resulting in changes in diffusivity

Fig. 106.11. The practical use of DWI and ADC maps is also demonstrated in this 38-year-old female, in whom the conventional images suggested the diagnosis glioblastoma multi- forme. The patient showed no sign of infectious disease either clinically or biochemically. The upper two images, T2-weighted and T1-weighted with contrast, show a multicystic lesion in the right frontal lobe, with edema and ring enhancement. The Trace images and ADC map on the lower row show that within the cysts water diffusion is severely restricted, indicating a possi- ble abscess, which was confirmed at surgery

have to be considered, such as cellular density and swelling in acute inflammation or infection (multiple sclerosis, acute disseminating encephalomyelitis, vi- ral encephalitis), restriction of water movement in acute intramyelinic edema (posterior reversible en- cephalopathy syndrome) and vacuolating myelinopa- thy in toxic and metabolic conditions (maple syrup urine disease, Canavan disease, megalencephalic leukoencephalopathy with subcortical cysts, heroin intoxication, hexachlorophene intoxication, CO in- toxication), and axonal swelling in neurodegenerative and traumatic disorders (amyotrophic lateral sclero- sis, wallerian degeneration, diffuse axonal injury).

106.4 Brain Maturation and DWI–DTI Changes

DWI and DTI have the unique capability to show changes in anisotropy.Anisotropy is largely due to the presence of myelinated fiber tracts. It has been shown, however, that changes in anisotropy (FA) oc- cur before myelination becomes visible, confirming that anisotropy is partly the result of precursors of myelin and, probably more importantly, axonal or fiber density. The changes in FA in different brain areas have been extensively documented. FA shows an increase over time, while ADC values drop. Unfortu- nately the methods used to establish timetables are

not quite comparable. Measures such as “apparent”

anisotropy are less well defined than FA and RA and less reproducible. ADC values may also differ accord- ing to the machine and pulse sequences used, for ex- ample due to the b value setting and the number of applied diffusion gradients. Roughly, the ADC values are high in neonates, different in different anatomic regions, varying from 1.05 to 1.64 ¥ 10

mm

/s.At the age of about 10 months this range is in the order of 0.75 to 0.92 ¥ 10

mm

/s, close to values seen in young adults (Table 106.1).

A difficulty with reporting on quantitative diffu- sion data in neonates and children is that few of the data are obtained by methods that fully account for the effects of diffusion anisotropy. ADC values are of- ten obtained by measurements in one direction only.

When anisotropy is present, these estimations are not accurate. Even when measurements are made in three orthogonal directions, it is not possible to accurately and quantitatively determine anisotropy. The full dif- fusion tensor must be sampled in at least six different directions. Another concern is partial volume averag- ing in structures close to CSF spaces, because this will artificially increase the measured ADC values. Nu- merical data available at this moment should be applied with great care in clinical situations.

The development of anisotropy is reflected in the FA values in Table 106.2.

106.5 Hypoxic–Ischemic Conditions in Neonates

DWI and DTI have a great impact on the diagnosis of post-hypoxic–ischemic changes in neonates. On conventional MR sequences patterns of hypoxic–is- chemic encephalopathy in preterm and term neo- nates are often difficult to visualize in the immediate postnatal period. This is due to the only partly myeli- nated state of the neonate’s brain, with a high signal on T

-weighted images of the unmyelinated parts, obscuring the lesion. DWI often reveals the abnormal areas with high sensitivity. In particular the extent of lesions in early periventricular leukomalacia, in the cortico-subcortical pattern, and in basal ganglia

106.5 Hypoxic–Ischemic Conditions in Neonates 847

Table 106.1. ADC values in full-term neonates (adapted from Neil et al. 1998)

Region ADC values

(¥ 10^–3mm²/s) White matter centrum semiovale 1.30–1.60 Head of caudate nucleus 1.18–1.31

Insular gray matter 1.12–1.24

Lentiform nucleus 1.15–1.22

Thalamus 1.01–1.15

Anterior limb internal capsule 1.14–1.24 Posterior limb internal capsule 1.03–1.09 Cerebellar hemisphere 1.07–1.14

Table 106.2. Regional FA values at different ages (adapted from Schneider et al. 2004)

2 Months 12 Months 24 Months 144 Months

Genu corpus callosum 0.41 0.52 0.63 0.72

Splenium corpus callosum 0.45 0.61 0.68 0.76

Frontal white matter 0.16 0.29 0.34 0.39

Centrum semiovale 0.28 0.38 0.42 0.53

Posterior internal capsule 0.52 0.63 0.68 0.76

lesions can be visualized within hours after the insult (Fig. 106.12). When interpreted with care, DWI and DTI data are extremely helpful.

As an example, the values in periventricular leuko- malacia are instructive, because they seem to allow early confirmation of the presence of the lesions (Table 106.3).

Fig. 106.12. Images of a term-born neonate with acute pro- found hypoxia–ischemia. The upper row of conventional T2- weighted images show generalized edema, including swollen and abnormal basal ganglia. The lower two rows of DWI–Trace

images demonstrate the typical cortico-subcortical pattern, allowing an early diagnosis with a poor prognosis. It may take much longer before this pattern emerges on conventional im- ages

Table 106.3. ADC values in early periventricular leukomalacia (¥ 10^–3mm²/s) (adapted from Bozzao et al. 2003)

Region Non-PVL PVL

Posterior limb internal capsule 1.06 0.96

Corona radiata 1.23 0.97

Frontal white matter 1.35 1.19

Parietal white matter 1.52 1.15

PLV, periventricular leukomalacia

106.6 Leukoencephalopathies

DWI and DTI have been applied extensively in multi- ple sclerosis. In most studies estimation of FA and ADC has been used to compare different forms of multiple sclerosis and different tissue components, such as plaques, white matter around plaques, nor- mal-appearing white matter, and enhancing versus nonenhancing lesions. Some of the results are sum- marized in Table 106.4.

From Table 106.4 it is clear that the discriminating power of FA is considerably greater than that of ADC.

As expected, an increase in ADC is linked to a de- crease of FA.

The findings in normal-appearing white matter of a high ADC and low FA correspond with findings in MTR and MRS studies. DWI and MTR findings corre- late better with the disability scores of multiple scle- rosis patients than do conventional MR estimates and even lesion load estimations. In primary progressive multiple sclerosis conventional MR abnormalities are minimal. DTI reveals abnormal values of FA and ADC in the corpus callosum and internal capsule of these patients. Hypointense lesions on T

-weighted images, known as black holes and indicating a poor progno- sis, have the lowest diffusivity of all multiple sclerosis lesions. T

isointense lesions have the highest FA of all lesions studied and apparently have maintained tis- sue integrity.

Normal-appearing gray matter in multiple sclero- sis has also been the subject of a number of studies. In histogram analysis of diffusivity of gray matter in pa- tients with primary progressive multiple sclerosis, patients with secondary progressive multiple sclero- sis, and controls, statistically significant differences were found. The ADC and FA values in normal-ap- pearing gray matter are respectively higher and lower than in controls, although the differences are less pro- nounced than in white matter. The differences be- tween patients with primary progressive multiple sclerosis and controls were clearly less than between secondary progressive multiple sclerosis patients and controls, but still significant.

DWI and DTI have a place in research on patients with inherited leukoencephalopathies, but have also obtained a place in the clinical work-up of this cate-

gory of patients. Some findings of DWI and DTI have direct implications for the management of patients.

An important example is found in X-linked adreno- leukodystrophy. DTI can play a role in the detection of early abnormalities in patients, not yet seen on con- ventional images. Early changes are important in esti- mating when to offer the patient hematopoietic stem cell transplantation. DWI and DTI should be com- pared in this respect with MRS and magnetization transfer imaging.

In progressive inherited disorders the time factor plays an important role. In early metachromatic leukodystrophy ADC values are low and DWI shows a high signal. This effect is not completely understood, but is thought to be related to the accumulation of abnormal metabolites (sulfatides). In later phases of the disease,ADC increases and FA decreases as sign of disintegration of affected structures. Similar findings are reported in globoid cell leukodystrophy.

The type of underlying pathology is important. In maple syrup urine disease with neonatal onset, myelin vacuolation occurs in all myelinated parts of the brain in the newborn. These parts show low ADC values with about 80% decrease, and very high signal intensity on DWI (Fig. 106.13). In other disor- ders, such as nonketotic hyperglycinemia, Kearns–

Sayre syndrome, Canavan disease,

-2-hydroxyglutar- ic aciduria, and heroin encephalopathy, intramyelinic edema is also present and supposed to be the cause of restricted water movement and low ADC values in the early phase of the disease. In chronic myelin vacuola- tion, as seen in megalencephalic leukoencephalo- pathy with subcortical cysts and the end stages of Canavan disease, no evidence of restriction of water diffusion is found, but increased diffusion is found (Fig. 106.14).

Among the white matter disorders in children, hy- pomyelination is a frequent finding. It is striking that whereas the signal intensity of cerebral white matter is high on T

-weighted images in both hypomyelina- tion and demyelination, diffusion anisotropy can distinguish the two. Whereas diffusion anisotropy decreases in diseases characterized by myelin loss, marked diffusion anisotropy remains present in hy- pomyelinating conditions. This is an argument sug- gesting that it is not just myelination of fiber tracts that is responsible for the anisotropy, but rather that the tracts themselves are responsible (Fig. 106.15).

The combination of the nature of white matter changes and the changes over time in the lesion dic- tates the findings on DWI and DTI, usually expressed as ADC and FA values. This largely explains the con- troversies in reports on ADC and FA findings in sev- eral disorders, in particular posterior reversible en- cephalopathy syndrome and some inborn errors of metabolism.An example is found in the reports in the literature on ADC values in mitochondrial en- cephalopathy with lactate acidosis and stroke-like

106.6 Leukoencephalopathies 849

Table 106.4. FA and ADC in different multiple sclerosis lesions (from Guo et al. 2002)

Lesions FA ADC

(¥ 10^–3mm²/s)

Plaque 0.280 1.03

Periplaque white matter 0.383 0.79 Normal-appearing

white matter 0.493 0.74

Control white matter 0.537 0.73

Fig. 106.13.

episodes (MELAS). Both low and high ADC values have been found in fresh lesions (Fig. 106.16). This could depend on the delay between the insult and the measurement. It could also mean that MELAS pro- duces two different types of lesions, of which the

infarctions have low ADC values and follow the time course and structural changes seen in common in- farctions of vascular origin, whereas the “other” le- sions with high ADC values shortly after the insult represent another type of pathology, yet to be eluci- dated.

In ischemic white matter lesions, for example sub- cortical arteriosclerotic encephalopathy, loss of struc- tural integrity is expressed by a relatively high ADC (1.12 ± 15 ¥ 10

mm

/s) and moderately low FA val- ues (0.480–0.530). Figures in the same order have been obtained in patients with CADASIL. In these vascular disorders there is a strong correlation be- tween the measure of loss of integrity and results of cognitive tests.

106.6 Leukoencephalopathies 851

Fig. 106.13. A neonate with maple syrup urine disease. The pathological substrate is a vacuolating myelinopathy, which only affects myelinated areas. On the T2-weighted images (first and second rows) the myelinated parts of the brain show swelling and higher signal intensity than the surrounding un- myelinated structures. The differentiation of abnormal from normal tissue can be optimized by Trace diffusion-weighted imaging (third and fourth rows). Note that the optic tract and chiasm are also myelinated at this stage

䊴

Fig. 106.14. Images of an infant with Canavan disease at the ages of 4 months (upper row) and 12 months (lower row). Ini- tially the ADC values in the affected white matter areas are low.

In the following months they become much higher than the values of normal tissue. Canavan disease is characterized by a

vacuolating myelinopathy, as is maple syrup urine disease, ini- tially with compression of the extracellular space and restrict- ed diffusion. The increase in ADC values probably indicates that the tissue disintegrates and becomes rarefied over time

Fig. 106.15.

106.6 Leukoencephalopathies 853

Fig. 106.15. A series of T2- (first row) and T1-weighted (second row) images of a 6-year-old boy with Pelizaeus–Merzbacher disease, showing severe hypomyelination. Unlike what one would expect, Trace diffusion-weighted images (b value 1000, third row) do not add much information and the ADC values (fourth row) are close to normal: ADC of frontal white matter is 0.76–0.84, that of the basal ganglia 0.54–0.84, and that of the cortex 0.84–0.89 ¥ 10³mm²/s

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Fig. 106.16. A 12-year-old boy with MELAS develops a stroke- like episode, initially with dysphasia, followed by hemianopia.

The ADC map is most informative, showing a high ADC in the

temporal infarction and a low ADC in the occipital infarction, suggesting the influence of time on the ADC