Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Cortical stimulation mapping wikipedia , lookup
Dual consciousness wikipedia , lookup
Neuropsychopharmacology wikipedia , lookup
Hereditary hemorrhagic telangiectasia wikipedia , lookup
Brain damage wikipedia , lookup
Hemiparesis wikipedia , lookup
Chapter 10 (pp 139-167) of Multiple Sclerosis 2 - Blue Books of Practical Neurology, vol. 27. J.H Noseworthy, W.I. McDonald (eds.). Elsevier Science (USA), 2003. Magnetic Resonance Imaging and Spectroscopy: Insights into the Pathology and Pathophysiology of Multiple Sclerosis. Zografos Caramanos†, A. Carlos Santos†*, and Douglas L. Arnold† † Magnetic Resonance Spectroscopy Unit, Montreal Neurological Institute, McGill University, Montreal, Canada * Department of Clinical Medicine Imaging Center, Ribeirao Preto Medical School, University of Sao Paulo, Brazil 1. INTRODUCTION Since the time that Ormerod, du Boulay, and McDonald wrote their chapter on the neuroimaging of multiple sclerosis (MS ) for the first edition of this volume1, continuing advances in the field of magnetic resonance (MR) and MR imaging (MRI) have made tremendous impacts in our understanding of this disease2. Over the last few years, findings from (i) “conventional” MRI techniques [e.g., T 2-weighted imaging, proton-density-weighted imaging, and T 1-weighted imaging] – as well as those from (ii) more-recently developed “non-conventional” MRI techniques [e.g., magnetization-transfer imaging (MTI), diffusion-weighted imaging (DWI), diffusion-tensor imaging (DTI), proton magnetic resonance spectroscopy (1H-MRS ), and functional MRI (fMRI)] and (iii) MRI-based estimates of brain and spinal cord atrophy – have converged with findings from other areas of MS research (e.g., histopathological and clinical research) in order to give us a more comprehensive picture of MS pathology and pathophysiology. Given that a number of excellent reviews have been written on this topic in recent years3-9, the purpose of the present chapter is to describe some of the MRI techniques that are most-commonly used in the study of MS and to summarize some of the main aspects of our MRI-based understanding of MS. First, however, we will briefly review some of the relevant aspects of our current understanding of the pathology and pathophysiology of MS. 1.1. THE PATHOLOGY AND PATHOPHYSIOLOGY OF MULTIPLE S CLEROSIS The pathological hallmark of MS is the presence of demyelinating lesions (also referred to as MS plaques) within the central nervous system (CNS ) that are disseminated in both space and time10. Acute and sub-acute plaques are associated with acute inflammation and myelin breakdown. Chronic plaques are welldemarcated areas within the white matter that are hypocellular and characterized by myelin loss and astrocytic scar-formation11. Although usually described as being “relatively spared,” axons are injured and their density is decreased in both these types of demyelinating lesions. The overt, symptomatic “attacks” of MS that signal the usual initial “relapsing-remitting” (RR) stage of the disease are generally attributed to focal inflammation, which is associated with axonal injury and demyelination that result in slowing and/or blockade of axonal conduction. Conversely, the remission of symptoms during this stage is generally attributed to a combination of (i) the resolution of inflammation, (ii) the insertion of new sodium channels across demyelinated segments of axons, and (iii) the remyelination of axons. The majority of patients will eventually enter a “secondary-progressive” (S P) stage of the disease in which there is progressive neurological disability that is speculated to result from (i) the eventual failure of remyelination, (ii) gliosis, and (iii) irreversible axonal injury and degeneration. Indeed, as reviewed by Rieckmann and Smith12 and by Bjartmar and Trapp13, MS is no longer viewed as simply being a disease of inflammation and demyelination of the white matter: rather, axonal degeneration and neuronal damage throughout the brain are now accepted as being prominent features of MS – even early on in the disease. 1.2. S OME RECENT MRI-BASED INSIGHTS INTO MULTIPLE S CLEROSIS As we will soon see, insights into the pathology and pathophysiology of MS have been greatly advanced by information obtained using MRI. For example, it is now evident that the socalled “normal-appearing” white matter (NAWM, i.e., white matter that appears normal on gross pathological examination or on conventional MRI) in patients with MS is, in fact, far from normal; this is true both on appropriate histological analysis 14; 15, as well as on non-conventional MRI measures including MTI16, DWI17, DTI18, and 1H-MRS19; 20. Indeed, further changes in patients’ NAWM may become visible on these measures months – if not years – before the lesions associated with their MS become detectable on conventional MRI: this is true for MTI21, DWI22, and 1 H-MRS23; 24. In addition to this pathology of NAWM, there is now growing evidence for a significant involvement of the normal-appearing grey matter (NAGM) of the cerebral cortex in MS. Again, this is true both on histological analysis 25; 26, as well as on non-conventional MRI measures including MTI16; 27; 28, DWI29, and 1H-MRS30; 31. Furthermore, there is now evidence from fMRI for adaptive cortical reorganization in patients with MS in the absence of neurological impairment: a finding which suggests that the extent of corticofunctional pathology is greater than that which is manifest clinically 20; 32-34. Finally, there is also now MRI-based evidence that brain and spinal cord atrophy (which reflect destructive, irreversible pathology) are common – even early on in the course of the disease35. Page 1 of 18 Of course, all of these aforementioned MR measures that have contributed to our increased understanding of MS are only surrogate markers for different aspects of the pathological changes that accompany the disease. In order to better appreciate what changes in these MR surrogates mean, we will now review some of the MR techniques that are currently being used to study MS – first the conventional ones and then the non-conventional ones. We will then go on to review some of the findings regarding MRI-based analyses of cerebral atrophy in patients with MS. 2. CONVENTIONAL MAGNETIC RESONANCE IMAGING TECHNIQUES The conventional MRI techniques used to study MS patients produce images that reflect the physico-chemical state of protons that are present mainly in the water in the tissue that is being imaged. Contrast in such images is derived primarily from tissuespecific differences in the relaxation times, T1 (i.e., the time constant for the recovery of magnetization in the direction of the magnetic field) and T2 (i.e., the time constant for the decay of magnetization in the plane perpendicular to the magnetic field). (For a review of MRI theory and applications see Gadian36). These conventional MRI techniques include (i) T 2-weighted imaging, (ii) proton-density-weighted imaging, (iii) fluid-attenuated inversion-recovery imaging, (iv) standard T 1-weighted imaging, and (v) gadolinium-enhanced T 1-weighted imaging – each of which is described below. Figure 10-1 presents examples of images obtained using these techniques in patients with MS. 2.1. T2-WEIGHTED IMAGING MR images are T 2-weighted by allowing more time for signal decay to occur due to T 2 relaxation during a relatively-long echo time (TE). Signals from water protons located in tissues associated with longer T 2 values decay less during a long TE; because of this, such tissues appear hyperintense on T 2-weighted images relative to tissues with shorter T 2 values. T 2 is prolonged in most pathologies that are associated with (i) inflammatory edema or tissue destruction (i.e., pathologies that increase bulk water that has less interaction with macromolecules) or (ii) gliosis in the white matter of the brain. For these reasons, MS lesions are hyperintense on T 2-weighted scans both in the early stages of the disease (i.e., when inflammation is most prominent) as well as in the later stages of the disease (i.e., when tissue injury and gliosis are more prominent). 2.1.1. T2-Weighted Imaging of Multiple Sclerosis Consistent with well-known pathological observations, the T 2weighted MR appearance of MS (see Figure 10-1) is primarily one of multiple, hyperintense white-matter lesions with periventricular predominance37. (See Narayanan et al38 for an example of the probabilistic mapping of MS lesions). Because of their exquisite sensitivity to subtle changes in water, T 2-weighted hyperintensities can even identify regions of brain tissue that appear normal on gross pathology and that are only associated with a very subtle infiltration of inflammatory cells 39. 2.1.1.1. Evolution of T 2-Weighted Hyperintense Lesions New lesions that are seen on T 2-weighted imaging [or on proton-density-weighted imaging (see below)] have a characteristic evolution40. Typically, they reach a maximum size in approximately four weeks, decrease in size over the next six to eight weeks, and leave a residual T 2-weighted abnormality37 that is a permanent record of tissue injury 5. For this reason, the total lesion volume that can be measured on such scans is often used as a surrogate measure of disease burden in MS. Furthermore, changes across time in the number and volume of lesions that are visible on T 2-weighted imaging can be used as indicators of disease activity and of response to treatment. It should be noted, however, that such changes in volume consist partly of inflammatory edema that eventually resolves with an associated decrease in the volume of T 2-weighted abnormality41. 2.1.1.2. Clinical Significance of T 2-Weighted Hyperintense Lesions Although the relationship between T 2-weighted imaging abnormalities and abnormal findings on histological examination is strong37; 39, the correlation between total cerebral T 2-weighted lesion load and clinical disability at any given time is only modest42; 43. Nevertheless, the predictive value of T 2-weighted lesions for the future development of clinically-definite MS is strong – particularly over the long term. For example, Brex et al44 recently published the latest results of an ongoing, longitudinal study that had, at that point, followed a group of 71 patients for 14 years from the time of their initial episode of presumed CNS-demyelination. They found that clinically-definite MS eventually developed in 44 of the 50 patients with T 2-weighted lesions at presentation (but in only 4 of 21 patients that had presented with normal MRI). Furthermore, the number and the volume of T 2-weighted lesions at baseline, as well as the change in lesion volume over the first 5 years, correlated significantly with the patients’ degree of long-term disability as measured by the EDSS (i.e., Kurtzke’s Expanded Disability Status Scale45). The latter correlations were, however, of only moderate strength – suggesting that, on its own, T 2-weighted lesion data cannot be used to make strong predictions about the prognosis in a patient that is known to have MS. The modest correlation seen between T 2-weighted lesion load and concurrent clinical disability may be explained by several factors: (i) the lack of pathological specificity of T 2-weighted abnormality, (ii) the fact that neurological disability is not easy to quantify and that the instruments used to do so (primarily the EDSS) are limited in their scope (e.g., the EDSS is based primarily on ambulatory ability), (iii) the fact that lesions in different CNS locations would be expected to correlate differently with disabilities in different spheres of CNS function (e.g., cerebral lesion-load is only weakly related to the sensorimotor dysfunction that results from spinal cord lesions – a dissociation that increases as the MS disease process progresses 46), and (iv) the fact that lesions may not be the only pathology responsible for disability, particularly late in the disease when a neurodegenerative process may develop 13. The correlation between T 2-weighted lesion volume and disability is also weakened by (v) the potential of the brain to functionally adapt to injury 20; 32-34 and (vi) the fact that focal lesions have diffuse consequences 19; 38. Thus, it is not surprising that it has been difficult to demonstrate a strong, direct effect of the localization of cerebral Page 2 of 18 T 2-weighted lesions on specific EDSS-measured functional impairments47. Nevertheless, there are examples of specific functional deficits that have been shown to correlate with the T 2weighted lesion load that is present in the region of the CNS associated with those particular functions (e.g., olfactory function48, sustained complex-attention and verbal workingmemory 49, and visual function50). Centrum Semiovale T2-weighted image PD-weighted image T1-weighted image Gd-enhanced image PD-weighted image T1-weighted image Gd-enhanced image Lateral Ventricles T2-weighted image Figure 10-1. Cross-sectional slices through the centrum semiovale (top) and the lateral ventricles of a patient with multiple sclerosis (MS) as seen on T 2-weighted, proton-density-weighted (PD), T 1-weighted, and gadolinium-enhanced T 1-weighted images. Of note at the level of the centrum semiovale: (i) many of the hyperintense lesions that can be seen on the T 2- and PD-weighted images are also seen as hypointensities on the T 1-weighted images and (ii) two of these lesions are still active and inflammatory (as evidenced by the ring-like Gd-enhancement). Of note at the level of the lateral ventricles: (i) it is difficult to discriminate between the periventricular lesions and cerebrospinal fluid (CSF) on the T 2-weighted image, (ii) it is easy to discriminate between the periventricular lesions and the CSF on the PD-weighted image; (ii) the extent of T 2- and PD-weighted hyperintensity is much more extensive than the hypointensities seen on the T 1-weighted images; and (iii) there are no active, inflammatory lesions at this level (as evidenced by the lack of Gd-enhancement). (Images are courtesy of the Canadian MS/BMT Study Group). 2.1.1.3. T2-Weighted Hypointensities In addition to the T 2-weighted white-matter hyperintensities that we have dealt with thus far, grey-matter hypointensity on T 2weighted imaging of patients with MS (which is thought to reflect pathologic iron deposition and brain degeneration) has also been described51 and shown to be related to clinical status52; 53 and prognosis 54 in MS. 2.2. PROTON -DENSITY-WEIGHTED IMAGING Because both lesions and cerebrospinal fluid (CSF) are hyperintense on T 2-weighted images, the discrimination of periventricular lesions can be difficult. One way of increasing this discrimination is to acquire images with, so-called, “proton-density weighting” 55. Such images do not actually reflect the density of protons; they do, however, have intermediate T 1- (see below) and Page 3 of 18 T 2-weightings that, as shown in Figure 10-1, result in the CSF appearing dark (because its long T 1 value predominates over its long T 2) and lesions appearing bright (because their long T 2 values predominate over their relatively shorter T 1). 2.3. FLUID-ATTENUATED INVERSION -RECOVERY IMAGING Another means of increasing contrast between CSF and lesions is through the use of fluid-attenuated inversion-recovery (FLAIR) images 55. This approach involves the use of an inversion pulse to suppress the signal arising from bulk water in the CSF 56. FLAIR images provide both (i) better discrimination between ventricular CSF and the periventricular T 2-weighted-hyperintensities that are associated with MS lesions and (ii) increased contrast for lesions – particularly for those that are cortical or juxtacortical57. 2.4. T1-WEIGHTED IMAGING T 1-weighted images are produced by shortening the TR (i.e., the amount of time between successive repetitions of water-proton excitation) and, thereby, allowing less time for water to regain its equilibrium magnetization. Water protons in tissues with a relatively short T 1 recover more quickly and produce more signal at relatively-short TR than do those in tissues with a longer T 1. Protons in bulk water (e.g., in CSF, or in tissue that is associated with either extracellular edema or with a loss of structural integrity) have a long T 1 and, as shown in Figure 10-1, appear hypointense on T 1-weighted sequences. T 1-weighted images are less sensitive to changes in either watercontent or gliosis than are T 2-weighted images. Nevertheless, acute, inflammatory lesions can sometimes be associated with so much edema that they can show substantial T 1-weighted hypointensity. Chronic T 1-weighted hypointensities are, however, much more specific indicators of tissue destruction than are T 2-weighted hyperintensities 58-60. The term “black hole” has been used to describe hypointense lesions on T 1-weighted images 61. Given the fact, however, that this term is typically used to imply an association with irreversible tissue destruction, use of the term is probably best reserved for lesions that are chronically-hypointense on T 1-weighted imaging. Only about 30% of new T 2-weighted lesions will evolve into chronic black holes 62. 2.4.1. T1-Weighted Imaging of Multiple Sclerosis Given the increased pathological specificity associated with T 1weighted hypointensity, it is not surprising that lesions that show this feature on T 1-weighted imaging are more strongly correlated to disability in MS than are lesions that are T 1-isointense43; 59; 61. In a recent study, Cid et al63 examined the relationship between RR-MS patients’ (i) degree of lesion hypointensity on T 1-weighted imaging obtained at the time of an MS relapse, (ii) change in EDSS score between the time of the relapse and one month later, and (iii) amount of neuronal apoptosis induced on neuronal cultures by CSF obtained at the time of the relapse. They found a strong relationship between T 1-weighted lesion hypointensity and both (i) poor recovery from relapse and (ii) the amount of neuronal apoptosis induced by the CSF. weighted imaging can be increased with the injection of a chelated form of gadolinium (Gd), which interacts with water so as to shorten its T 1 relaxation time. Normally, Gd does not cross the blood-brain barrier (BBB). However, focal inflammation in the CNS – as occurs during an MS attack – is often associated with an “opening” of the BBB65. This opening allows Gd to pass through in a manner that is graded depending upon (i) the extent of the associated increase in BBB permeability, (ii) the dose of Gd administered, and (iii) the interval between Gd-injection and T 1weighted MR acquisition (i.e., the time available for the Gd to leak across the BBB)66; 67. 2.5.1. Gd-Enhanced T1-Weighted Imaging of Multiple Sclerosis The acute inflammatory process that was described above is transient. As a result, Gd only causes MS lesions to enhance for two to six weeks after they become detectable by conventional MRI 66; 68. Thus, a useful role for Gd-enhanced T 1-weighted imaging is to help distinguish recently-appearing, inflammatory lesions from ones that are more chronic (and no longer associated with sufficient inflammation to result in Gd enhancement). Indeed, MRI assessment of disease activity in MS is often based upon the number of Gd-enhancing lesions that are seen within a T 1-weighted scan. The majority of enhancing lesions are “nodular,” but about 25% of lesions show “ring-like” enhancement 69. Such ring-enhancing lesions are associated with a more-severe clinical outcome and it has been suggested that they reflect a more-destructive pathology 70. Most lesions that are Gd-enhancing on T 1-weighted images continue to be detectable on T 2-weighted images after the acute inflammation (and, thus, the Gd-enhancement) have resolved. Conversely, it is generally believed that (i) most T 2-weighted lesions in the central white matter of MS patients are associated with an initial, variable period of Gd-enhancement on T 1-weighted imaging and (ii) Gd-enhancing lesions and T 2-weighted lesions represent two different stages of a single pathological process. There is evidence, however, to suggest that some of the lesions on T 2-weighted images can develop independently of Gdenhancement 71 – perhaps because of (i) ongoing low-grade inflammation that is not detected with Gd-enhancement or (ii) mechanisms other than inflammation that are responsible for progression in some existing lesions. 2.5.1.1. Clinical Significance of Gd-Enhancement About 50% of patients with MS will have at least one Gdenhancing lesion at any given time. Surprisingly, in what is referred as the “clinico-radiological paradox,” a large proportion of these lesions are not associated with clinical manifestations: indeed, on average, Gd-enhancing lesions occur about ten times more frequently than clinical relapses 3; 72; 73. Despite the striking difference between the frequency of new Gd-enhancing lesions and the frequency of clinical exacerbations, there is still, however, a strong relationship between them74. Furthermore, the number of enhancing lesions on a single scan is (i) predictive of subsequent relapse-rate and (ii) is correlated with both subsequent enhancinglesion activity and change in T 2-weighted lesion load75. 2.5. GADOLINIUM-ENHANCED T1-WEIGHTED IMAGING As reviewed by Rovaris and Filippi64, signal intensity on T 1- Although the presence of one or more Gd-enhancing brain Page 4 of 18 lesions is predictive of conversion to clinically definite MS76, Gdenhancement is not a strong predictor of the development of cumulative impairment or EDSS-measured disability74. These findings are consistent with the hypothesis that different pathogenetic mechanisms may be responsible for (i) the occurrence of relapses and (ii) the development of long-term disability. MT(on) MT(off) with saturation pulse B A 3. % MTr Image without saturation pulse B A [1-(MTon / MToff)] x 100 B A NON-CONVENTIONAL MAGNETIC RESONANCE IMAGING TECHNIQUES Even though the aforementioned conventional-MRI techniques have allowed us to image MS lesions with much greater sensitivity, these techniques are not capable of fully characterizing and quantifying the extent of tissue damage in patients with MS. A number of recently-developed MR techniques are better suited for such a role. These techniques include: (i) MTI, (ii) DWI, (iii) DTI, (iv) 1H-MRS, and (v) fMRI – each of which are, in turn, described below. Figure 10-2. Examples of T 1-weighted images obtained during a magnetization transfer (MT) study of a patient with multiple sclerosis. Images are obtained both with (Mton) and without (MToff) the presence of a saturation pulse, and MT ratios are calculated as shown. Note that the MToff image is just a standard T 1-weighted image and MTR values are more reduced in lesions that are more hypointense on this image (e.g., compare A and B). (Images are courtesy of Dr. G.B. Pike). 3.1. MAGNETIZATION -TRANSFER IMAGING Protons associated with molecules that are large and less mobile than water (e.g., the macromolecules that make up cell membranes) have a very short T 2 and are not visible on conventional MRI; this is because their signals decay completely before conventional MRI data is acquired. The effect of these protons can, however, be observed indirectly by the phenomenon of magnetization transfer (MT)77. In MTI, appropriate radio-frequency pulses are applied to selectively saturate the magnetization of the bound protons. This saturated magnetization is then naturally exchanged with those protons that are found in the relatively “mobile” protons of CSF, extracellular water, and intracellular water (i.e., the protons that are normally observed by MRI). This transfer of saturated magnetization to the MRI-observable, free-water pool results in a reduction of the signal intensity from the observable protons to a degree that depends upon (i) the nature and density of the macromolecules at a given location and (ii) their interaction with bulk water. In the white matter of the CNS, the MT effect is dominated by the large surface area of myelin, and changes in MT are considered more specific for demyelination78; 79 than are changes in either T 2 or T 1 relaxation times. It should be noted that MT is also sensitive to changes in bulk water that are associated with edema80-82 as well as to macromolecular changes associated with injury to other cell types (e.g., axons60; 83). Thus, changes in MT should not be considered pathologically specific. An important advantage of MTI is that it can be easily quantified by calculating the magnetization-transfer ratio (MTR), which is the relative MRI signal intensity measured in the absence of a saturating pulse compared to the intensity that is measured in the presence of a saturating pulse (see Figure 10-2). A low MTR indicates less exchange of magnetization between tissue macromolecules and the surrounding water molecules. 3.1.1. MTI of Multiple Sclerosis MTR values are typically reduced in MS lesions in a manner that is consistent with the degree of T 1-weighted hypointensity60; 84; 85 , which, as we have seen, is related to tissue destruction; thus, lesions that are larger and more destructive have lower MTR values than lesions that are smaller and less destructive. Furthermore, greater reductions in MTR values are seen in lesions that are more inflammatory 86. In addition to the MTR changes observed in MS lesions, numerous studies have also reported decreased MTR in the NAWM of MS patients compared to the white matter of healthy normal controls 21; 85; 87-89. Greater decreases in MTR are found in patients with SP-MS than in patients with RR-MS90-92, and these decreases are related to both increasing EDSS-measured disability43; 93 and increasing cognitive impairment 94. 3.1.1.1. Temporal Evolution of Lesions on MTI Because MTI produces very reproducible MTR values for a given pulse sequence, it can be used to quantify the pathological evolution of MS lesions over time. Such longitudinal MTI studies have shown that, even before the detection of lesions is possible on proton-density- or T 2-weighted images, MTR values have begun to decline in the NAWM that is found at these locations21; 95; 96. Then, as lesions begin to demonstrate Gd-enhancement on T 1-weighted imaging, there is an explosive decrease in the lesional MTR values due to a combination of inflammatory edema and demyelination; this may be followed by either (i) a stabilization of lesional MTR values at these lower levels, (ii) a recovery of lesional MTR values several weeks after the initial decrease, or, in a small number of lesions, (iii) a continuing decrease in local MTR values 97-99. The recovery of MTR or its continued decline may be related, respectively, to remyelination or to chronic activity of lesions. Thus, MTR provides a potentially powerful tool for exploring lesion evolution in MS. 3.1.1.2. Clinical Significance of MTI The fact that MTR focal abnormalities in NAWM develop Page 5 of 18 before the appearance of lesions implies that MTI might provide information that could predict the future evolution of MS. This has led to the assessment of the predictive value of MTI in MS. For example, the prognostic value of MTI was recently examined by Santos et al100,who found that mean NAWM-MTR values were able to successfully predict whether or not levels of disability would increase at five-year follow-up in patients with relativelylong-standing MS; importantly, MTR values within these individuals’ T 2-weighted lesions could not predict such changes. In a related study of patients with a clinically-isolated syndrome suggestive of MS, Iannucci et al101 found that MTR values at the time of presentation were significant predictors of the development of clinically-definite MS within the next 25-42 months (although not as strong predictors as these patients’ presenting T 2-weighted lesion volumes). On the other hand, Brex et al102 found that mean NAWM-MTR values in a similar group of patients could not predict whether these individuals would go on to have MS in the following 12 months (at which point, these newly-diagnosed MS patients still had normal NAWM-MTR). Thus, while it is clear that MTI has prognostic value in MS, further studies are necessary to better characterize its strengths and limitations. As reviewed by Filippi and Inglese106, the pathology associated with MS modifies the water self-diffusion characteristics in the CNS by altering the geometry and/or the permeability of structural barriers that are found therein. The application of DWI techniques to the study of MS is appealing in that they can provide a quantitative estimate of the degree of fiber disruption and, thus, potentially provide information on the mechanisms that lead to irreversible disability in this disease. 3.2.1. DWI of Multiple Sclerosis DWI studies have consistently shown that the ADC107; 108 and of water is (i) higher in MS lesions than in NAWM (see D Figure 10-3) and (ii) higher in acute lesions than in chronic lesions. Such studies have also consistently demonstrated that mean D values are increased in the NAWM of MS patients compared to those observed in the white matter of healthy normal controls – a finding that hold true in the brain17; 110; 111, the spinal cord112, and the NAGM 16. 109 PD-Weighted Image Mean Diffusivity Image Fractional Anisotropy Image 3.1.1.3. MTI of Normal-Appearing Grey Matter As mentioned in the introduction, there is now an increasing appreciation that, at the microscopic level, there is substantial lesional pathology of the NAGM in patients with MS25; 26. The lesions in NAGM are associated with much less inflammation and demyelination than are the lesions in the white matter26. Perhaps related to this, as well as to their size and to their location (i.e., adjacent to CSF), these lesions in the NAGM are largely undetected by current conventional MRI techniques. Thus, it is important that, in addition to the MTI changes in the lesional and normal-appearing white matter of patients with MS, reductions in MTR values have also been found in the NAGM of patients with MS relative to normal controls 16; 27; 28. Together, these findings suggest that the pathological process that is at work in the brains of patients with MS is very diffuse and is not tissue-specific. 3.2. DIFFUSION -WEIGHTED IMAGING As reviewed by Cercignani and Horsfield103, DWI allows for the in vivo measurement of the diffusion of water in the CNS due to Brownian motion. Because both the axolemma and the myelin sheath restrict water diffusion in nerve fibers104, pathological processes (such as those at work in MS) that modify the integrity of such tissues can result in a loss of restricting barriers and, thereby, increase the so-called “apparent diffusion coefficient” (ADC) of water. The ADC is a measure of the random displacement of water molecules in a particular direction. Because of the restricting entities that are found in biological tissues, ADC values in the CNS are lower than the diffusion coefficient of pure water (hence the term “apparent diffusion coefficient of water”). A measure of diffusion that is independent of the orientation of structures is provided by the mean diffusivity index, D . Also referred to as the directionallyaveraged ADC (or ADCavg) or trace, D is the average of the ADCs measured in three orthogonal directions. (For a review of DWI theory and applications see, for example, Schaefer et al105). * * * * * * * * * * * * * * * * ** ** ** ** ** * ** ** Figure 10-3. Cross-sectional slices through the lateral ventricles of a patient with multiple sclerosis as seen on proton-densityweighted (PD), diffusion-weighted, and diffusion-tensor imaging (which is reviewed in the next section). The asterisks point out the lesions that are seen as (i) hyperintensities on PD-weighted imaging, (ii) increased mean diffusivity ( D ) values on diffusion-weighted imaging, and (iii) decreased fractional anisotropy (FA) values on diffusion-tensor imaging. (Images are courtesy of J.S.W. Campbell). D values have been shown to correlate with individual MS patients’ EDSS scores 113-116 and disease durations114-116. Furthermore, D values are higher in patients with SP-MS than in those with RR-MS116; 117. Increases in lesional D values correlate with hypointensity on T 1-weighted images 116, and ring-enhancing lesions on Gd-enhanced T 1-weighted images have higher mean D values than do nodular-enhancing lesions118 – a pattern that corresponds to reported histopathological differences between these types of lesions70. Interestingly, individual patients’ D values are not significantly related to their MTR values 119 and are only moderately related to decreases in their 1H-MRS-measured NA/Cr values 120 (the relevance of which is explained in the section on 1H-MRS below). These findings suggest that MTI provides information about different aspects of brain pathology in MS than do these other two imaging techniques (i.e., MTI and 1H-MRS). Page 6 of 18 3.2.1.1. Temporal Evolution of Lesions on DWI Serial DWI studies have also been used in order to investigate the changes in NAWM that precede the development of acute MS lesions. For example, Rocca et al121 found that regions of NAWM that would subsequently become Gd-enhancing lesions had a significant increase in their mean D values starting six weeks prior to the appearance of enhancement. Furthermore, Werring et al22, who acquired a years’ worth of monthly DWI scans in MS patients, observed (i) a steady and moderate increase in mean NAWM D values that was followed by (ii) a rapid and marked increase at the time of Gd-enhancement and (iii) a slow decay after the end of enhancement. These two studies suggest that new focal lesions that are associated with an eventual breakdown of the BBB are preceded by subtle, progressive alterations in tissue integrity that are below the resolution of conventional MRI. Interestingly, Werring et al22 also found that there was a mild increase in the mean D values of NAWM regions that were contralateral and homologous to the NAWM regions that evolved into Gd-enhancing lesions (but that themselves did not become lesional) – a finding that supports the concept that structural damage in lesions can cause disturbances in connected areas of NAWM 122. 3.3. DIFFUSION -TENSOR IMAGING The ADC of water in biological tissue that has a regular and ordered microstructure depends upon the direction along which it is measured (i.e., it is anisotropic)103. Thus, D (which has a magnitude but no direction) does not provide a complete description of the diffusion phenomenon. A full characterization can, however, be obtained in terms of a tensor (i.e., a matrix of numbers) that describes the diffusion of water in three dimensions. From such a tensor it is possible to derive an index of diffusion anisotropy – the most commonly-used index being that of fractional anisotropy (FA123; 124). FA values obtained using DTI reflect the degree of cellular-structure alignment within the tissue that is being imaged. In the normal brain, FA images show a marked difference between (i) grey matter and CSF (which are both virtually isotropic) and (ii) white matter (which has a variable degree of anisotropy)125. Maximum FA values are found in white-matter regions that are characterized by a strongly-ordered parallel arrangement of fibers, whereas much lower values are found in regions where white matter fibers have incoherent orientations or where fiber-bundles cross. In DTI voxels that are normally full of highly-ordered fibers, a relative decrease in diffusion anisotropy could signal structural disintegration within the CNS and could be used to detect both focal damage to major neuronal pathways as well as remote damage resulting from Wallerian degeneration126. It should be noted that DTI would be expected to be less sensitive to such damage in voxels that contained less-ordered tissue or that contained crossing fibers. 3.3.1. DTI of Multiple Sclerosis Results similar to those found using DWI have also been found using DTI in patients with MS. For example, as shown in Figure 10-3, DTI measures of FA have been shown to be decreased in the NAWM of patients with MS18; 29; 126; 127 and to be even more decreased in lesions18; 126; 127 – the greatest FA decreases typically being found in the most destructive (i.e., T 1-weighted hypointense) lesions18; 126; 127. Similar to the D findings described above119, there is also a lack of relationship between individual MS patients’ FA values and their MTR values 128; 129 – further suggesting that diffusion imaging and MTI provide somewhat independent measures of brain pathology in MS. Interestingly, whereas significant negative relationships have been found between individuals’ EDSS scores and their FA values 18; 29; 127, abnormalities in FA have not yet been found in RR-MS at the very early stages of their disease130 and mean FA difference have not yet been found between different MS subgroups16; 18; 29. If this is not simply the result of a low sensitivity of DTI for detecting structural damage, this would imply that the disability in RR-MS has a basis more in dysfunction than in loss of structural integrity. 3.4. PROTON MAGNETIC RESONANCE S PECTROSCOPY None of the water-based imaging methods that we have reviewed so far can provide pathological specificity for injury to a particular cell type. Pathological specificity for injury to neurons and neuronal processes (i.e., axons and dendrites) can, however, be provided by quantification of the neuronal marker compound, Nacetylaspartate (NAA) using 1H-MRS131. 1 H-MRS is fundamentally different from the water-protonbased MRI techniques that we have discussed thus far in that it records signals that arise from protons in metabolites that are present in brain tissue at concentrations approximately one thousand times lower than that of tissue water132. Whereas the signal-to-noise ratio and image resolution that is possible with these metabolite-based images is much lower than that for water-based images, the resulting images can provide chemico-pathological specificity that is not possible with conventional MR images. The various approaches to in vivo 1H-MRS include: (i) single-voxel 1HMRS studies (in which proton spectra are acquired from a single volume) and (ii) 1H-MRS imaging (1H-MRSI) studies [in which proton spectra are obtained from multiple volume elements (i.e., voxels) at the same time]. 3.4.1.1. 1 H-MRS Metabolites of Interest As shown in Figure 10-4, the water-suppressed, localized 1HMRS spectrum of the normal human brain that is recorded at relatively-long echo times (usually 136 - 272 ms) reveals three major resonance peaks [the locations of which are expressed as the difference in parts per million (ppm) between the resonance frequency of the compound of interest and that of a standard compound (i.e., tetramethylsilane)]. These peaks are commonly ascribed to the following metabolites: (i) tetramethyl amines (Cho), which resonate at 3.2 ppm and are mostly choline-containing phospholipids that participate in membrane synthesis and degradation; (ii) creatine and phosphocreatine (Cr), which resonate at 3.0 ppm and play an important role in energy metabolism; and (iii) N-acetyl groups (NA), which resonate at 2.0 ppm and are comprised primarily of the neuronally-localized NAA. A fourth peak usually arising from either the methyl resonance of lactate (LA) or lipids (which both resonate at 1.3 ppm), is normally onlybarely visible above the baseline noise but can be detected in certain pathological conditions. Spectra acquired at shorter echo times (e.g., 30 ms) are better for detecting resonances that have a short T 2 (e.g., Page 7 of 18 lipids and inositol). Unfortunately, such short-T 2 1H-MRS records broad, overlapping signals that complicate the quantification of such spectra. Normal Control Patient with MS NA [1] NWM [1] NAWM NA/Cr = 3.83 Cho/Cr = 1.30 NA/Cr = 2.86 NA Cho/Cr = 1.84 Cho Cho Cr Cr 1 1 [2] NWM 2 NA/Cr = 3.04 Cho/Cr = 1.14 [2] Lesion NA 2 NA/Cr = 1.91 Cho/Cr = 1.12 NA Cho Cr Cho Cr Figure 10-4. Proton-density-weighted magnetic resonance images through the centrum semiovale and the results of proton magnetic resonance spectroscopic imaging (1H-MRSI) in a normal control subject and in a patient with multiple sclerosis. The superimposed grid in each image represents individual 1H-MRSI voxels, and the large, thick, white box represents the entire 1H-MRSI volume of interest for that individual. The smaller, numbered boxes represent voxels of normal-appearing white matter (NAWM) and lesional brain tissue in the patient and normal white matter (NWM) in the normal control subject. The 1H-MRSI spectra from within each of these voxels is shown to the right of each image. The areas under the NA and Cho peaks (normalized to Cr) are shown above each spectrum. The spectra have been scaled so that the Cr peak in each of them has the same height. Note (i) the decrease in NA/Cr values from the patient’s NAWM voxel relative to the NWM voxels in the control subject, (ii) the even greater decrease in lesional NA/Cr, and (iii) the increased Cho/Cr in the patient’s NAWM voxel, which may be predictive of a soon-to-appear lesion in that location. The simplest approach to the quantitation of 1H-MR spectra is to normalize the NA and Cho signal intensities to the signal intensity from Cr in the same voxel131. Of course, this latter method does not provide absolute quantification and, importantly, the resulting measures of relative concentration are only valid if the underlying pathology does not substantially affect the local concentration of Cr. Thus, it is important that Cr concentrations are relatively constant throughout normal brain tissue and that they have also been shown to be relatively constant in both the lesions133; 134 and the NAWM 134-136 of patients with MS. It should be noted , however, that Cr values have been shown to decrease in acute133 and severely-hypointense lesions136: thus, it is inappropriate to normalize within-lesion NA and Cho values to within-lesion Cr values in either acute lesions or T 1-weighted black holes. The limitations of ratio-based quantitation can be overcome by the various methods of semi-absolute quantification that have been developed137; 138. Unfortunately, such methods have their own limitations; for example, (i) they are dependent on many assumptions, (ii) they can be difficult to carry out, and (iii) they tend to have more variance than those based on ratios 3.4.2. 1 H-MRS of Multiple Sclerosis The resonance intensity that is ascribed to NAA is, arguably, the most important 1H-MRS signal in the characterization of MS pathology because NAA is localized exclusively within neurons and neuronal processes such as axons and dendrites 139; 140. Although NAA has been found in cell cultures of oligodendroglial cell lineage 141; 142, this appears to be a phenomenon that is limited to cell cultures. Indeed, the specificity of NAA as an axon-specific marker in vivo, even in the presence of injury and significant density of oligodendroglial cell precursors, has been confirmed in a recent biochemical and immunohistochemical study of rat optic nerve transection143. Furthermore, the validity of NAA as a surrogate for axonal density in MS has been confirmed in studies that correlated (i) findings from in vivo 1H-MRSI and histopathological analysis of cerebral biopsy specimens144 and (ii) findings from HPLC and histopathological analysis of spinal cord biopsy specimens145. 3.4.2.1. NA/Cr 1 H-MRSI-measured NA/Cr values have been used to quantify neuronal and axonal integrity in vivo in the brains of patients with MS for over a decade now146; 147. 1H-MRS studies have shown that periventricular NA/Cr values are low in both the lesions and, to a lesser extent, the NAWM of patients with MS19; 122; 147; 148. Patients with SP-MS are more affected than those with RR-MS19; 149. Interestingly, however, this latter finding seems to be related more to NA/Cr differences in NAWM than in lesions19. Importantly, just as with MTI and DWI, 1H-MRSI-measured values of NA/Cr within the cortical NAGM of patients with MS have also been shown to be decreased relative to those in the cortical grey matter of healthy normal controls 30; 31. Decreases in MS patients’ periventricular-NA/Cr values are strongly related to both their disease duration and their EDSS scores 149. Importantly, the correlation between patients’ EDSS scores and their periventricular NA/Cr values is as strong, or stronger, than that of any other MRI measure150 – a relationship that becomes even stronger when EDSS scores are correlated with estimates of NA/Cr in pure periventricular NAWM 19; 20. In addition to correlating with patient’s EDSS scores (which are greatly influenced by a patients’ ambulatory status), periventricular-NA/Cr values in MS patients have also been shown to be strongly related to their cognitive abilities 151. 3.4.2.2. Other Metabolites In addition to NA, several other 1H-MRS resonance intensities are also important in understanding the MS disease process. For example, 1H-MRS-observed Cho and lipid peaks are thought to provide important information regarding myelin breakdown in the MS disease process23; 148. Furthermore, the presence of myoinositol has been proposed as a marker of glial cells and gliosis 30. 3.4.2.3. Temporal Evolution of Lesions on 1H-MRS As with MTI and DWI, the earliest abnormalities that are visible on 1H-MRS occur months before the appearance of Gdenhanced or T 2-weighted lesions. For example, regions of NAWM that will go on to become lesions have been shown to be associated with locally-increased levels of both Cho24 and lipids23 – both of which are markers of abnormality in cell membranes. As newly- Page 8 of 18 developing lesions become detectable on conventional MRI, they are associated with focal inflammation, demyelination, and axonal injury – pathological processes that result in decreases to NA/Cr values 148; 152-154, further increases to Cho/Cr values 148; 152-154, and acutely-increased LA/Cr values 148. Importantly, these NA-related decreases may persist chronically – particularly in the core of chronic lesions148. On the other hand, the presence of LA is more common in lesions that are Gd-enhancing154 and seems to resolve within weeks148. Increases in Cho/Cr are pronounced in Gd-enhancing lesions153; 154 and may remain elevated for years148, but eventually return to normal136; 148. 3.4.2.4. Spatial Distribution of 1H-MRSI Pathology Changes in 1H-MRSI metabolites are greatest in the core of lesions and decrease with increasing distance from their center148. Importantly, they do not end at the edge of the T 2-weighted abnormality but extend into the surrounding NAWM 148. For example, in the hyper-acute phase of the lesion (i.e., when it is still expanding), both the decrease in NA/Cr and the increase in Cho/Cr can be found around the lesion in the NAWM that is well beyond the expanding T 2-weighted abnormality. It is still not clear if the NAWM abnormalities in patients with MS result from (i) the sum of the remote effects of focal, lesional pathology or (ii) an independent process that is more diffuse. been shown to be even more related to FA and NA/Cr values that are measured specifically within the periventricular NAWM 20 – implying that NAWM changes are more specifically related to functional change than those in non-segmented periventricular brain tissue (which contains NAWM, NAGM, and lesions). This reorganized cortico-motor activation has been found in regions of the brain that are usually only activated in the execution of morecomplex motor tasks – suggesting that such activation reflects, at least in part, disinhibition of latent motor pathways that are “recruited” to limit any functional impairment related to the tissue damage associated with MS157. Individual patients’ levels of activation within these recruited areas have been shown to be related to their (i) EDSS scores, (ii) disease duration, (iii) extent and number of spinal cord lesions, (iv) brain and spinal-cord MTR, (v) whole-brain D , and (vi) and whole-brain FA157. Together, these findings suggest that compensation due to adaptive cortical changes can contribute to sustaining motor functions during the early stages of MS; as a result, the actual extent of cortico-functional pathology in patients with MS may be greater than that which is clinically evident. Normal Control MS Patient 1 w/ Low Disability, Normal NA/Cr MS Patient 2 w/ Low Disability, Low NA/Cr 3.5. FUNCTIONAL MAGNETIC RESONANCE IMAGING fMRI is another MR technique that differs fundamentally from the others discussed so far. For example, the blood-oxygen level dependent method of fMRI (a widely-used approach to such an analysis) exploits the fact that hemoglobin and deoxyhemoglobin are magnetically different such that hemoglobin shows up better on MRI images than does deoxyhemoglobin155. Brain activation is associated with increased blood flow and greater blood oxygenation that, in turn, produce an increased MR signal. fMRI involves (i) the acquisition of a series of such MR images of the brain in quick succession and (ii) the statistical analysis of these images in order to quantify subtle changes in the functional state of the brain across time. Figure 10-5. Examples of fMRI activation maps (in white) obtained during a simple finger-flexion motor task and registered on to anatomical MR images for a normal control subject, a multiple sclerosis (MS) patient with normal periventricular NA/Cr, and an MS patient with abnormallylow periventricular NA/Cr. Both patients were able to perform the task without difficulty and had low disability ratings. Note the larger, bilateral extent of functional activation in the patient with low NA/Cr. (Images are courtesy of Dr. P.M. Matthews). 3.5.1. fMRI of Multiple Sclerosis Thus far, fMRI has been used in patients with MS to study abnormal patterns of brain activation that occur during the performance of simple motor tasks20; 32-34; 156; 157. These studies have shown that, as with other forms of brain injury, there is adaptive cortical reorganization in patients with MS as evidenced by extended, bilateral activation in motor-related regions (as opposed to the more-constrained, mostly-unilateral activation that is seen in normal controls during the tasks that have been used in these studies). Reddy et al156 combined findings from fMRI of a simple fingerflexion task with those from 1H-MRSI. As shown in Figure 10-5, they demonstrated that the extent of this functional reorganization [as expressed in the form of a lateralization index (LI) that reflected the degree of bilateral versus unilateral functional-activation] was strongly related to the presence of axonal injury (as measured by decreased periventricular NA/Cr on 1H-MRSI). LI values have since 4. MR-BASED ASSESSMENT OF BRAIN ATROPHY Atrophy of the brain or spinal cord at post mortem examination is one of the pathological hallmarks of irreversible CNS damage. As reviewed by Simon35, with the advent of MRI, it is now possible to assess CNS atrophy in vivo using a variety of measures that include, for example, (i) ventricular enlargement, (ii) grey- and white-matter volumes, and (iii) the use of more-global measures such as (a) the brain parenchymal fraction (BPF, i.e., the ratio of brain parenchymal volume to the total volume within the surface contour of the brain)158 or (b) BICCR (i.e., the ratio of brain parenchymal volume within the surface contour of the inner table of the skull)159. Page 9 of 18 4.1.1. Atrophy in Multiple Sclerosis CNS atrophy in patients with MS has been documented since the original autopsy examinations of such individuals – with atrophy having been shown to reflect (i) injury and loss of both (a) neurons and their processes and (b) oligodendrocytes and the myelin that they produce, as well as (ii) changes in the supporting matrix that result from the contraction of glial tissue35. Until recently, such atrophy has generally been thought of as occurring late in the disease35; this view has changed, however, with the development of neuroimaging techniques that have demonstrating atrophy in the majority of patients with MS – even at very early stages of the disease158; 160; 161. 4.1.1.1. Clinical Significance of CNS Atrophy The average amount of accumulated spinal cord atrophy has been shown to be greater in patients with SP-MS than in patients with RR disease162-165. Similarly, as a group, SP-MS patients have also been shown to have smaller brain volumes, and larger lateral ventricles, than RR-MS patients159; 166 (see Figure 10-6). Normal Control Patient with RR-MS Patient with SP-MS Figure 10-6. Cross-sectional slices through the lateral ventricles of a normal control subject, a patient with relapsing-remitting multiple sclerosis (RR-MS), and a patient with secondaryprogressive multiple sclerosis (SP-MS) as seen on T 2-weighted imaging. Note (i) the high degree of atrophy seen even in the early stage of the disease (as evidenced visually by the ventricular enlargement in the RR-MS patient as compared to the control subject) and (ii) the even-greater degree of atrophy that is seen in the secondary-progressive stage of the disease (as evidenced visually by the sulcal enlargement, the decreased volume of the white- and grey-matter, and the furtherincreased ventricular enlargement in the SP-MS patient). Brainstem and upper-spinal-cord atrophy have been shown to be strongly correlated with EDSS scores in patients with MS164; 167. This may, in part, be due to the fact that atrophy in these regions can be related to Wallerian degeneration following damage to the cerebrum, to the spinal cord, or to both. Moderate correlations have also been found between individuals’ EDSS scores and their degrees of (i) callosal atrophy 42; 168, (ii) cerebral white-matter atrophy 162, and (iii) ventricular enlargement 42; 169-172. On the other hand, correlations between EDSS scores and brain-parenchyma-based estimates of atrophy have been variable – ranging from strong158; 159; 173 to non-significant 115; 174; 175. It should be noted that MRI measures of brain volume and atrophy have been also shown to be significantly related to the presence of depression176, impaired quality of life177, and cognitive decline173; 178 in patients with MS. 4.1.1.2. Rate of Atrophy Brain atrophy develops at a remarkably-high rate in patients with MS35. For instance, Fox et al179 showed that (i) the yearly rate of cerebral atrophy in their MS group (0.8% per year) was over twice that of normal controls (0.3%) and (ii) the yearly rate of ventricular enlargement in patients was almost five times greater than in the controls (1.6 versus 0.3 cc per year). Furthermore, Simon et al180 studied 85 RR-MS patients with mild-to-moderate disability over the course of two years and found that (i) the volume of the lateral ventricles increased at a rate of 5.5% per year and (ii) the area of the corpus callosum decreased at a rate of 4.9% per year. The course of cerebral atrophy in these patients was related to prior inflammatory disease activity as indicated by the presence of Gd-enhancing, T 1-weighted lesions at baseline. Analysis of a subset of these patients (n=72) found a yearly decrease of 0.61% in their BPF, which translated to a yearly loss of approximately 8 cc per year158. There is some preliminary evidence to suggest that the rate of atrophy in patients with RR-MS differs from that in patients with SP-MS in a region-specific manner181; 182. For example, SP-MS patients seem to have a significantly-faster rate of atrophy around the ventricles than patients with RR-MS – suggesting a greater relative volume change along the long projection tracts182. On the other hand, the rate of spinal cord atrophy has been reported to be faster in patients with RR-MS164. These findings suggest that CNS atrophy may not be a uniform process and that different regions may have distinct responses to disease progression. 4.1.1.3. Relationship of Atrophy to Other MRI Measures As might be expected, CNS atrophy in patients with MS has been shown to be related to many of the other MRI-measures that we have reviewed in this chapter. For example, patients’ supratentorial brain volumes have been shown to be significantly related to their load of hypointense lesions on T 1-weighted imaging183; 184. Similarly, patients’ numbers of Gd-enhancing T 1weighted lesions have been shown to be well-correlated with an increase in their ventricular size166; 185 – especially in patients with a high proportion of ring-enhancing lesions185. Furthermore, in two related longitudinal studies, Luks et al172 found that patients’ total numbers of new Gd-enhancing lesions were related to their monthly changes in ventricular volume, and Simon et al180 found that the degree of cerebral atrophy observed over a two-year period (as indicated by ventricular enlargement and callosal atrophy) was greater for patients that had entered their trial with Gd-enhancing lesions. It should be noted, however, that not all studies have found a relationship between Gd-enhancement and atrophy 186. The relationship of atrophy with T 2-weighted lesion load has also been somewhat inconsistent. For example, whereas some groups have found a significant relationship between their patients’ T 2-hyperintense lesion load and their (i) degree of ventricular enlargement 162, (ii) callosal atrophy 162, and (iii) overall brain volume90, others have been unable to find a significant relationship with their patients’ supratentorial brain volumes 183; 184. Page 10 of 18 The relationship between cerebral atrophy and the newer, nonconventional MRI measures seems to be more consistent. For example, brain volume has been shown to correlate with both (i) MTR values within normal-appearing brain tissue90 and (ii) D values within the brain parenchyma115. Furthermore, Collins et al159 found that cerebral atrophy (as measured by BICCR values) was correlated with periventricular axonal injury (as measured by decreases in 1H-MRSI NA/Cr values) in their group of patients with SP-MS. BICCR values in their group of mildly-disabled patients with RR-MS were not reduced relative to their normal control group, even though this group of patients did have significantly reduced NA/Cr values. Together, these findings suggest that microscopic and biochemical changes in the brains of patients with MS are related to the decreases in brain volume that are found in such individuals; importantly, however, there seems to be a decoupling between axonal damage and atrophy in the very early stages of the disease. 4.1.1.4. Caveats It should be noted that current MRI analysis techniques allow for the measurement of small changes in volume on the order of 0.2% of total brain volume – changes of magnitude that are much smaller than those that can be identified on gross pathological examination. Thus far, it has been tempting to (i) assume that these small changes in brain volume have the same pathological significance as gross atrophy post mortem and (ii) suggest that they provide a measure of a specific pathological feature such as axonal loss. Unfortunately, it is not clear that this is always the case: for example, myelin loss, glial- and matrix-related changes, as well as shifts in water distribution all occur in MS and may be associated with volume changes of this magnitude. Although it is clear that volume measurements must contribute in some way to estimating the full extent of irreversible axonal damage in MS, further investigations are required to understand the precise pathological significance of atrophy and the mechanisms that contribute to its progression. 5. SUMMARY AND CONCLUSIONS MS, consistent with the emerging view that the pathology in this disease is relatively diffuse and not specifically tied to the white matter. Importantly, the amount of such microscopic, pathological change in any individual patient is highly related to their degree of concurrent disability and is also related to future changes in their disability. Second, certain pathological changes in NAWM can foreshadow the appearance of the focal lesions that are classically associated with MS. Third, there is significant cortico-functional reorganization that takes place in the brains of patients with MS; a reorganization that, at least at the early stages of the disease, seems to have the potential to be functionally-adaptive and compensate for some of the effects of the ongoing neuropathological processes that are associated with the disease. Fourth, all of these changes are occurring in parallel with the progressive CNS atrophy, even in the early course of the disease. Although findings from MRI have taught us much about the MS disease process over the sixteen years since the publication of the first edition of this volume, we still have much to learn about the spatial and temporal dynamics of the lesional and non-lesional pathological tissue that characterizes the MS brain. It is the hope and goal of the present authors that a multimodal, multiparametric approach to the analysis of longitudinal data obtained from a combination of conventional and non-conventional imaging techniques will become commonplace. Such an approach still has much to teach us about the spatial and temporal characteristics of the MS disease process, and the knowledge that it will provide us with will undoubtedly lead to better methods of treating and monitoring MS. REFERENCES 1. Ormerod IEC, du Boulay GH, McDonald WI. Imaging of multiple sclerosis. In McDonald WI, Silberberg DH (eds). Multiple Sclerosis. Bodmin, Cornwall: Butterworth & Co. (Publishers), 1986. 2. Matthews PM, Arnold DL. Magnetic resonance imaging of multiple sclerosis: new insights linking pathology to clinical evolution. Curr Opin Neurol 2001; 14; 3: 279-87. As we have seen, our understanding of the pathology and pathophysiology of MS has been greatly advanced by information obtained using MRI. For example, the conventional MRI techniques that were described above have greatly increased the sensitivity with which lesions can be detected. In addition, they have also provided us with a great deal of in vivo information regarding the spatial distribution, temporal dynamics, and clinical significance of these lesions. Furthermore, the newer, non-conventional methods of MR acquisition and analysis that were also described above have allowed us to quantify in vivo the microscopic, molecular pathology; the biochemical changes; the cortico-functional adaptations; and the progressive atrophy that may occur in the brain and spinal cord of patients with MS. 3. Miller DH, Grossman RI, Reingold SC, McFarland HF. The role of magnetic resonance techniques in understanding and managing multiple sclerosis. Brain 1998; 121; Pt 1: 3-24. Based primarily on the findings from the non-conventional MRI methods that were reviewed in this chapter, a number of important insights regarding MS pathology and pathophysiology have become evident. First, there are significant pathological changes in the otherwise normal-appearing grey and white matter of patients with 7. Nyul LG, Udupa JK. MR image analysis in multiple sclerosis. Neuroimaging Clin N Am 2000; 10; 4: 799-816 ,x. 4. Paty DW, Moore GRW. Magnetic resonance imaging changes as living pathology in multiple sclerosis. In Paty DW, Ebers GC (eds). Multiple Sclerosis. Philadelphia: F.A. Davis, 1998. 5. Barkhof F, van Walderveen M. Characterization of tissue damage in multiple sclerosis by nuclear magnetic resonance. Philos Trans R Soc Lond B Biol Sci 1999; 354; 1390: 1675-86. 6. Frank JA. Advances in Multiple Sclerosis. In Drayer BP (ed). Neuroimaging Clinics of North America. Philadelphia: W. B. Saunders Company, 2000; 10(4). 8. Filippi M. Non-conventional MR techniques to monitor the evolution of multiple sclerosis. Neurol Sci 2001; 22; 2: 195-200. Page 11 of 18 9. Rudick RA. Evolving concepts in the pathogenesis of multiple sclerosis and their therapeutic implications. J Neuroophthalmol 2001; 21; 4: 279-83. 10. McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD, McFarland HF, Paty DW, Polman CH, Reingold SC, Sandberg-Wollheim M, Sibley W, Thompson A, van den Noort S, Weinshenker BY, Wolinsky JS. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol 2001; 50; 1: 1217. 11. Ludwin SK. The neuropathology of multiple sclerosis. Neuroimaging Clin N Am 2000; 10; 4: 625-48 ,vii. 12. Rieckmann P, Smith KJ. Multiple sclerosis: more than inflammation and demyelination. Trends Neurosci 2001; 24; 8: 435-7. 13. Bjartmar C, Trapp BD. Axonal and neuronal degeneration in multiple sclerosis: mechanisms and functional consequences. Curr Opin Neurol 2001; 14; 3: 271-8. 14. Evangelou N, Esiri MM, Smith S, Palace J, Matthews PM. Quantitative pathological evidence for axonal loss in normal appearing white matter in multiple sclerosis. Ann Neurol 2000; 47; 3: 391-5. 15. Evangelou N, Konz D, Esiri MM, Smith S, Palace J, Matthews PM. Regional axonal loss in the corpus callosum correlates with cerebral white matter lesion volume and distribution in multiple sclerosis. Brain 2000; 123; Pt 9: 1845-9. 16. Cercignani M, Bozzali M, Iannucci G, Comi G, Filippi M. Magnetisation transfer ratio and mean diffusivity of normal appearing white and grey matter from patients with multiple sclerosis. J Neurol Neurosurg Psychiatry 2001; 70; 3: 311-317. changes in multiple sclerosis: a serial diffusion MRI study. Brain 2000; 123; Pt 8: 1667-76. 23. Narayana PA, Doyle TJ, Lai D, Wolinsky JS. Serial proton magnetic resonance spectroscopic imaging, contrast-enhanced magnetic resonance imaging, and quantitative lesion volumetry in multiple sclerosis. Ann Neurol 1998; 43; 1: 56-71. 24. Tartaglia MC, Narayanan S, Stefano ND, Arnaoutelis R, Antel SB, Francis SJ, Santos AC, Lapierre Y, Arnold DL. Choline is increased in pre-lesional normal appearing white matter in multiple sclerosis. Neurology 2001; 56: Suppl 3, A460. (Abstr.) 25. Kidd D, Barkhof F, McConnell R, Algra PR, Allen IV, Revesz T . Cortical lesions in multiple sclerosis. Brain 1999; 122; Pt 1: 1726. 26. Peterson JW, Bo L, Mork S, Chang A, Trapp BD. Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Ann Neurol 2001; 50; 3: 389-400. 27. Ge Y, Grossman RI, Udupa JK, Babb JS, Kolson DL, McGowan JC. Magnetization transfer ratio histogram analysis of gray matter in relapsing-remitting multiple sclerosis. AJNR Am J Neuroradiol 2001; 22; 3: 470-5. 28. Ge Y, Grossman RI, Udupa JK, Babb JS, Mannon LJ, McGowan JC. Magnetization Transfer Ratio Histogram Analysis of NormalAppearing Gray Matter and Normal-Appearing White Matter in Multiple Sclerosis. J Comput Assist Tomogr 2002; 26; 1: 62-68. 29. Ciccarelli O, Werring DJ, Wheeler-Kingshott CA, Barker GJ, Parker GJ, Thompson AJ, Miller DH. Investigation of MS normal-appearing brain using diffusion tensor MRI with clinical correlations. Neurology 2001; 56; 7: 926-33. 17. Filippi M, Iannucci G, Cercignani M, Assunta Rocca M, Pratesi A, Comi G. A quantitative study of water diffusion in multiple sclerosis lesions and normal-appearing white matter using echoplanar imaging. Arch Neurol 2000; 57; 7: 1017-21. 30. Kapeller P, McLean MA, Griffin CM, Chard D, Parker GJ, Barker GJ, Thompson AJ, Miller DH. Preliminary evidence for neuronal damage in cortical grey matter and normal appearing white matter in short duration relapsing-remitting multiple sclerosis: a quantitative MR spectroscopic imaging study. J Neurol 2001; 248; 2: 131-8. 18. Filippi M, Cercignani M, Inglese M, Horsfield MA, Comi G. Diffusion tensor magnetic resonance imaging in multiple sclerosis. Neurology 2001; 56; 3: 304-11. 31. Sharma R, Narayana PA, Wolinsky JS. Grey matter abnormalities in multiple sclerosis: proton magnetic resonance spectroscopic imaging. Mult Scler 2001; 7; 4: 221-6. 19. Fu L, Matthews PM, De Stefano N, Worsley KJ, Narayanan S, Francis GS, Antel JP, Wolfson C, Arnold DL. Imaging axonal damage of normal-appearing white matter in multiple sclerosis. Brain 1998; 121; Pt 1: 103-13. 32. Reddy H, Narayanan S, Matthews PM, Hoge RD, Pike GB, Duquette P, Antel J, Arnold DL. Relating axonal injury to functional recovery in MS. Neurology 2000; 54; 1: 236-9. 20. Caramanos Z, Campbell JSW, Narayanan S, Francis SJ, Antel SB, Reddy H, Matthews PM, Sappey-Marinier D, Pike GB, Arnold DL. Axonal integrity and fractional anisotropy in the normalappearing white matter of patients with multiple sclerosis: Relationship to cerebro-functional reorganization and clinical disability. Proc Int Soc Magn Reson Med Submitted; (Abstr.) 21. Pike GB, De Stefano N, Narayanan S, Worsley KJ, Pelletier D, Francis GS, Antel JP, Arnold DL. Multiple sclerosis: magnetization transfer MR imaging of white matter before lesion appearance on T2-weighted images. Radiology 2000; 215; 3: 824-30. 22. Werring DJ, Brassat D, Droogan AG, Clark CA, Symms MR, Barker GJ, MacManus DG, Thompson AJ, Miller DH. The pathogenesis of lesions and normal-appearing white matter 33. Lee M, Reddy H, Johansen-Berg H, Pendlebury S, Jenkinson M, Smith S, Palace J, Matthews PM. The motor cortex shows adaptive functional changes to brain injury from multiple sclerosis. Ann Neurol 2000; 47; 5: 606-13. 34. Rocca MA, Colombo B, Comi G, Filippi M. fMRI changes in patients with relapsing-remitting MS and no clinical disability. Proc Int Soc Magn Reson Med 2001; 9: 256. (Abstr.) 35. Simon JH. Brain and spinal cord atrophy in multiple sclerosis. Neuroimaging Clin N Am 2000; 10; 4: 753-70 ,ix. 36. Gadian DG. NMR and its Applications to Living Systems, 2nd ed. Oxford: Oxford University Press, 1996. 37. Li DK, Zhao G, Paty DW. T2 hyperintensities: findings and significance. Neuroimaging Clin N Am 2000; 10; 4: 717-38 ,ix. Page 12 of 18 38. Narayanan S, Fu L, Pioro E, De Stefano N, Collins DL, Francis GS, Antel JP, Matthews PM, Arnold DL. Imaging of axonal damage in multiple sclerosis: spatial distribution of magnetic resonance imaging lesions. Ann Neurol 1997; 41; 3: 385-91. 39. De Groot CJ, Bergers E, Kamphorst W, Ravid R, Polman CH, Barkhof F, van der Valk P. Post-mortem MRI-guided sampling of multiple sclerosis brain lesions: increased yield of active demyelinating and (p)reactive lesions. Brain 2001; 124; Pt 8: 1635-45. multiple sclerosis: decreased signal in thalamus and putamen. Ann Neurol 1987; 22; 4: 546-50. 52. Bakshi R, Dmochowski J, Shaikh ZA, Jacobs L. Gray matter T2 hypointensity is related to plaques and atrophy in the brains of multiple sclerosis patients. J Neurol Sci 2001; 185; 1: 19-26. 53. Bakshi R, Shaikh ZA, Janardhan V. MRI T2 shortening ('black T2') in multiple sclerosis: frequency, location, and clinical correlation. Neuroreport 2000; 11; 1: 15-21. 40. Willoughby EW, Grochowski E, Li DK, Oger J, Kastrukoff LF, Paty DW. Serial magnetic resonance scanning in multiple sclerosis: a second prospective study in relapsing patients. Ann Neurol 1989; 25; 1: 43-9. 54. Bakshi R, Benedict RH, Bermel RA, Caruthers SD, Puli SR, Tjoa CW, Fabiano AJ, Jacobs L. T2 Hypointensity in the Deep Gray Matter of Patients With Multiple Sclerosis: A Quantitative Magnetic Resonance Imaging Study. Arch Neurol 2002; 59; 1: 62-68. 41. Isaac C, Li DK, Genton M, Jardine C, Grochowski E, Palmer M, Kastrukoff LF, Oger J, Paty DW. Multiple sclerosis: a serial study using MRI in relapsing patients. Neurology 1988; 38; 10: 15115. 55. Butman JA, Frank JA. Overview of imaging in multiple sclerosis and white matter disease. Neuroimaging Clin N Am 2000; 10; 4: 669-687. 42. Schreiber K, Sorensen PS, Koch-Henriksen N, Wagner A, Blinkenberg M, Svarer C, Petersen HC. Correlations of brain MRI parameters to disability in multiple sclerosis. Acta Neurol Scand 2001; 104; 1: 24-30. 56. Gawne-Cain ML, O'Riordan JI, Thompson AJ, Moseley IF, Miller DH. Multiple sclerosis lesion detection in the brain: a comparison of fast fluid-attenuated inversion recovery and conventional T2weighted dual spin echo. Neurology 1997; 49; 2: 364-70. 43. Barkhof F. MRI in multiple sclerosis: correlation with expanded disability status scale (EDSS). Mult Scler 1999; 5; 4: 283-6. 57. Bakshi R, Ariyaratana S, Benedict RH, Jacobs L. Fluid-attenuated inversion recovery magnetic resonance imaging detects cortical and juxtacortical multiple sclerosis lesions. Arch Neurol 2001; 58; 5: 742-8. 44. Brex PA, Ciccarelli O, O'Riordan JI, Sailer M, Thompson AJ, Miller DH. A longitudinal study of abnormalities on MRI and disability from multiple sclerosis. New England Journal of Medicine 2002; 346; 3: 158-164. 45. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 1983; 33; 11: 1444-52. 46. Narayanan S, De Stefano N, Francis GS, Tartaglia MC, Arnaoutelis R, Arnold DL. Disease duration influences the relationship between brain axonal injury, spinal cord atrophy, and disability in multiple sclerosis. Proc Int Soc Magn Reson Med 2000; 1: 297. (Abstr.) 47. Riahi F, Zijdenbos A, Narayanan S, Arnold D, Francis G, Antel J, Evans AC. Improved correlation between scores on the expanded disability status scale and cerebral lesion load in relapsingremitting multiple sclerosis. Results of the application of new imaging methods. Brain 1998; 121; Pt 7: 1305-12. 48. Zorzon M, Ukmar M, Bragadin LM, Zanier F, Antonello RM, Cazzato G, Zivadinov R. Olfactory dysfunction and extent of white matter abnormalities in multiple sclerosis: a clinical and MR study. Mult Scler 2000; 6; 6: 386-90. 49. Sperling RA, Guttmann CR, Hohol MJ, Warfield SK, Jakab M, Parente M, Diamond EL, Daffner KR, Olek MJ, Orav EJ, Kikinis R, Jolesz FA, Weiner HL. Regional magnetic resonance imaging lesion burden and cognitive function in multiple sclerosis: a longitudinal study. Arch Neurol 2001; 58; 1: 115-21. 50. Caruana PA, Davies MB, Weatherby SJ, Williams R, Haq N, Foster DH, Hawkins CP. Correlation of MRI lesions with visual psychophysical deficit in secondary progressive multiple sclerosis. Brain 2000; 123; Pt 7: 1471-80. 58. van Walderveen MA, Kamphorst W, Scheltens P, van Waesberghe JH, Ravid R, Valk J, Polman CH, Barkhof F. Histopathologic correlate of hypointense lesions on T1-weighted spin- echo MRI in multiple sclerosis. Neurology 1998; 50; 5: 1282-8. 59. Barkhof F, Karas GB, van Walderveen MA. T1 hypointensities and axonal loss. Neuroimaging Clin N Am 2000; 10; 4: 739-752. 60. van Waesberghe JH, Kamphorst W, De Groot CJ, van Walderveen MA, Castelijns JA, Ravid R, Lycklama a Nijeholt GJ, van der Valk P, Polman CH, Thompson AJ, Barkhof F. Axonal loss in multiple sclerosis lesions: magnetic resonance imaging insights into substrates of disability. Ann Neurol 1999; 46; 5: 747-54. 61. Truyen L, van Waesberghe JH, van Walderveen MA, van Oosten BW, Polman CH, Hommes OR, Ader HJ, Barkhof F. Accumulation of hypointense lesions ("black holes") on T1 spinecho MRI correlates with disease progression in multiple sclerosis. Neurology 1996; 47; 6: 1469-76. 62. van Walderveen MA, Truyen L, van Oosten BW, Castelijns JA, Lycklama a Nijeholt GJ, van Waesberghe JH, Polman C, Barkhof F. Development of hypointense lesions on T1-weighted spinecho magnetic resonance images in multiple sclerosis: relation to inflammatory activity. Arch Neurol 1999; 56; 3: 345-51. 63. Cid C, Alcazar A, Regidor I, Masjuan J, Salinas M, AlvarezCermeno JC. Neuronal apoptosis induced by cerebrospinal fluid from multiple sclerosis patients correlates with hypointense lesions on T1 magnetic resonance imaging. J Neurol Sci 2002; 193; 2: 103-9. 64. Rovaris M, Filippi M. Contrast enhancement and the acute lesion in multiple sclerosis. Neuroimaging Clin N Am 2000; 10; 4: 70516 ,viii-ix. 51. Drayer BP, Burger P, Hurwitz B, Dawson D, Cain J, Leong J, Herfkens R, Johnson GA. Magnetic resonance imaging in Page 13 of 18 65. Rubin LL, Staddon JM. The cell biology of the blood-brain barrier. Annu Rev Neurosci 1999; 22; 11-28. 66. Silver NC, Good CD, Barker GJ, MacManus DG, Thompson AJ, Moseley IF, McDonald WI, Miller DH. Sensitivity of contrast enhanced MRI in multiple sclerosis. Effects of gadolinium dose, magnetization transfer contrast and delayed imaging. Brain 1997; 120; Pt 7: 1149-61. 67. Tofts PS, Kermode AG. Measurement of the blood-brain barrier permeability and leakage space using dynamic MR imaging. 1. Fundamental concepts. Magn Reson Med 1991; 17; 2: 357-67. 68. Tortorella C, Codella M, Rocca MA, Gasperini C, Capra R, Bastianello S, Filippi M. Disease activity in multiple sclerosis studied by weekly triple-dose magnetic resonance imaging. J Neurol 1999; 246; 8: 689-92. 69. He J, Grossman RI, Ge Y, Mannon LJ. Enhancing patterns in multiple sclerosis: evolution and persistence. AJNR Am J Neuroradiol 2001; 22; 4: 664-9. demyelination in primates: preliminary in vivo study with MR and magnetization transfer. AJNR Am J Neuroradiol 1995; 16; 2: 225-31. 80. Dousset V, Grossman RI, Ramer KN, Schnall MD, Young LH, Gonzalez-Scarano F, Lavi E, Cohen JA. Experimental allergic encephalomyelitis and multiple sclerosis: lesion characterization with magnetization transfer imaging. Radiology 1992; 182; 2: 483-91. 81. Dousset V, Armand JP, Lacoste D, Mieze S, Letenneur L, Dartigues JF, Caill JM. Magnetization transfer study of HIV encephalitis and progressive multifocal leukoencephalopathy. Groupe d'Epidemiologie Clinique du SIDA en Aquitaine. AJNR Am J Neuroradiol 1997; 18; 5: 895-901. 82. Silver NC, Barker GJ, MacManus DG, Miller DH, Thorpe JW, Howard RS. Decreased magnetisation transfer ratio due to demyelination: a case of central pontine myelinolysis. J Neurol Neurosurg Psychiatry 1996; 61; 2: 208-9. 70. Morgen K, Jeffries NO, Stone R, Martin R, Richert ND, Frank JA, McFarland HF. Ring-enchancement in multiple sclerosis: marker of disease severity. Mult Scler 2001; 7; 3: 167-71. 83. Kimura H, Grossman RI, Lenkinski RE, Gonzalez-Scarano F. Proton MR spectroscopy and magnetization transfer ratio in multiple sclerosis: correlative findings of active versus irreversible plaque disease. AJNR Am J Neuroradiol 1996; 17; 8: 1539-47. 71. Lee MA, Smith S, Palace J, Narayanan S, Silver N, Minicucci L, Filippi M, Miller DH, Arnold DL, Matthews PM. Spatial mapping of T2 and gadolinium-enhancing T1 lesion volumes in multiple sclerosis: evidence for distinct mechanisms of lesion genesis? Brain 1999; 122; Pt 7: 1261-70. 84. Loevner LA, Grossman RI, McGowan JC, Ramer KN, Cohen JA. Characterization of multiple sclerosis plaques with T1-weighted MR and quantitative magnetization transfer. AJNR Am J Neuroradiol 1995; 16; 7: 1473-9. 72. McFarland HF, Frank JA, Albert PS, Smith ME, Martin R, Harris JO, Patronas N, Maloni H, McFarlin DE. Using gadoliniumenhanced magnetic resonance imaging lesions to monitor disease activity in multiple sclerosis. Ann Neurol 1992; 32; 6: 758-66. 85. Hiehle JF, Jr., Lenkinski RE, Grossman RI, Dousset V, Ramer KN, Schnall MD, Cohen JA, Gonzalez-Scarano F. Correlation of spectroscopy and magnetization transfer imaging in the evaluation of demyelinating lesions and normal appearing white matter in multiple sclerosis. Magn Reson Med 1994; 32; 3: 28593. 73. Miller DH, Barkhof F, Nauta JJ. Gadolinium enhancement increases the sensitivity of MRI in detecting disease activity in multiple sclerosis. Brain 1993; 116; Pt 5: 1077-94. 74. Kappos L, Moeri D, Radue EW, Schoetzau A, Schweikert K, Barkhof F, Miller D, Guttmann CR, Weiner HL, Gasperini C, Filippi M. Predictive value of gadolinium-enhanced magnetic resonance imaging for relapse rate and changes in disability or impairment in multiple sclerosis: a meta-analysis. Gadolinium MRI Meta-analysis Group. Lancet 1999; 353; 9157: 964-9. 86. Filippi M, Rocca MA, Rizzo G, Horsfield MA, Rovaris M, Minicucci L, Colombo B, Comi G. Magnetization transfer ratios in multiple sclerosis lesions enhancing after different doses of gadolinium. Neurology 1998; 50; 5: 1289-93. 87. Filippi M, Campi A, Dousset V, Baratti C, Martinelli V, Canal N, Scotti G, Comi G. A magnetization transfer imaging study of normal-appearing white matter in multiple sclerosis. Neurology 1995; 45; 3 Pt 1: 478-82. 75. Molyneux PD, Filippi M, Barkhof F, Gasperini C, Yousry TA, Truyen L, Lai HM, Rocca MA, Moseley IF, Miller DH. Correlations between monthly enhanced MRI lesion rate and changes in T2 lesion volume in multiple sclerosis. Ann Neurol 1998; 43; 3: 332-9. 88. Loevner LA, Grossman RI, Cohen JA, Lexa FJ, Kessler D, Kolson DL. Microscopic disease in normal-appearing white matter on conventional MR images in patients with multiple sclerosis: assessment with magnetization-transfer measurements. Radiology 1995; 196; 2: 511-5. 76. Brex PA, O'Riordan JI, Miszkiel KA, Moseley IF, Thompson AJ, Plant GT, Miller DH. Multisequence MRI in clinically isolated syndromes and the early development of MS. Neurology 1999; 53; 6: 1184-90. 89. Rocca MA, Mastronardo G, Rodegher M, Comi G, Filippi M. Long-term changes of magnetization transfer-derived measures from patients with relapsing-remitting and secondary progressive multiple sclerosis. AJNR Am J Neuroradiol 1999; 20; 5: 821-7. 77. van Buchem MA, Tofts PS. Magnetization transfer imaging. Neuroimaging Clin N Am 2000; 10; 4: 771-788. 90. Tortorella C, Viti B, Bozzali M, Sormani MP, Rizzo G, Gilardi MF, Comi G, Filippi M. A magnetization transfer histogram study of normal-appearing brain tissue in MS. Neurology 2000; 54; 1: 186-93. 78. Fralix TA, Ceckler TL, Wolff SD, Simon SA, Balaban RS. Lipid bilayer and water proton magnetization transfer: effect of cholesterol. Magn Reson Med 1991; 18; 1: 214-23. 79. Dousset V, Brochet B, Vital A, Gross C, Benazzouz A, Boullerne A, Bidabe AM, Gin AM, Caille JM. Lysolecithin-induced 91. Rovaris M, Bozzali M, Santuccio G, Iannucci G, Sormani MP, Colombo B, Comi G, Filippi M. Relative contributions of brain and cervical cord pathology to multiple sclerosis disability: a Page 14 of 18 study with magnetisation transfer ratio histogram analysis. J Neurol Neurosurg Psychiatry 2000; 69; 6: 723-7. 92. Filippi M, Inglese M, Rovaris M, Sormani MP, Horsfield P, Iannucci PG, Colombo B, Comi G. Magnetization transfer imaging to monitor the evolution of MS: a 1-year follow-up study. Neurology 2000; 55; 7: 940-6. 93. Dehmeshki J, Ruto AC, Arridge S, Silver NC, Miller DH, Tofts PS. Analysis of MTR histograms in multiple sclerosis using principal components and multiple discriminant analysis. Magn Reson Med 2001; 46; 3: 600-9. 94. Rovaris M, Filippi M, Minicucci L, Iannucci G, Santuccio G, Possa F, Comi G. Cortical/subcortical disease burden and cognitive impairment in patients with multiple sclerosis. AJNR Am J Neuroradiol 2000; 21; 2: 402-8. 95. Filippi M, Rocca MA, Martino G, Horsfield MA, Comi G. Magnetization transfer changes in the normal appearing white matter precede the appearance of enhancing lesions in patients with multiple sclerosis. Ann Neurol 1998; 43; 6: 809-14. 96. Goodkin DE, Rooney WD, Sloan R, Bacchetti P, Gee L, Vermathen M, Waubant E, Abundo M, Majumdar S, Nelson S, Weiner MW. A serial study of new MS lesions and the white matter from which they arise. Neurology 1998; 51; 6: 1689-97. 97. van Waesberghe JH, van Walderveen MA, Castelijns JA, Scheltens P, Lycklama a Nijeholt GJ, Polman CH, Barkhof F. Patterns of lesion development in multiple sclerosis: longitudinal observations with T1-weighted spin-echo and magnetization transfer MR. AJNR Am J Neuroradiol 1998; 19; 4: 675-83. 98. Dousset V, Gayou A, Brochet B, Caille JM. Early structural changes in acute MS lesions assessed by serial magnetization transfer studies. Neurology 1998; 51; 4: 1150-5. 106. Filippi M, Inglese M. Overview of diffusion-weighted magnetic resonance studies in multiple sclerosis. J Neurol Sci 2001; 186; Suppl 1: S37-43. 107. Larsson HB, Thomsen C, Frederiksen J, Stubgaard M, Henriksen O. In vivo magnetic resonance diffusion measurement in the brain of patients with multiple sclerosis. Magn Reson Imaging 1992; 10; 1: 7-12. 108. Christiansen P, Gideon P, Thomsen C, Stubgaard M, Henriksen O, Larsson HB. Increased water self-diffusion in chronic plaques and in apparently normal white matter in patients with multiple sclerosis. Acta Neurol Scand 1993; 87; 3: 195-9. 109. Tievsky AL, Ptak T, Farkas J. Investigation of apparent diffusion coefficient and diffusion tensor anisotrophy in acute and chronic multiple sclerosis lesions. AJNR Am J Neuroradiol 1999; 20; 8: 1491-9. 110. Cercignani M, Iannucci G, Filippi M. Diffusion-weighted imaging in multiple sclerosis. Ital J Neurol Sci 1999; 20; 5 Suppl: S246-9. 111. Werring DJ, Clark CA, Droogan AG, Barker GJ, Miller DH, Thompson AJ. Water diffusion is elevated in widespread regions of normal-appearing white matter in multiple sclerosis and correlates with diffusion in focal lesions. Mult Scler 2001; 7; 2: 83-9. 112. Clark CA, Werring DJ, Miller DH. Diffusion imaging of the spinal cord in vivo: estimation of the principal diffusivities and application to multiple sclerosis. Magn Reson Med 2000; 43; 1: 133-8. 113. Cercignani M, Inglese M, Pagani E, Comi G, Filippi M. Mean diffusivity and fractional anisotropy histograms of patients with multiple sclerosis. AJNR Am J Neuroradiol 2001; 22; 5: 952-8. 99. Filippi M. Magnetization transfer imaging to monitor the evolution of individual multiple sclerosis lesions. Neurology 1999; 53(5; Suppl 3): S18-22. 114. Tourbah A, Stievenart JL, Abanou A, Fontaine B, Cabanis EA, Lyon-Caen O. Correlating multiple MRI parameters with clinical features: an attempt to define a new strategy in multiple sclerosis. Neuroradiology 2001; 43; 9: 712-20. 100. Santos AC, Narayanan S, De Stefano N, Tartaglia MC, Francis SJ, Arnaoutelis R, Caramanos Z, Antel JP, Pike GB, Arnold DL. Magnetization transfer can predict clinical evolution in patients with multiple sclerosis. J Neurol In Press; 115. Wilson M, Morgan PS, Lin X, Turner BP, Blumhardt LD. Quantitative diffusion weighted magnetic resonance imaging, cerebral atrophy, and disability in multiple sclerosis. J Neurol Neurosurg Psychiatry 2001; 70; 3: 318-22. 101. Iannucci G, Tortorella C, Rovaris M, Sormani MP, Comi G, Filippi M. Prognostic value of MR and magnetization transfer imaging findings in patients with clinically isolated syndromes suggestive of multiple sclerosis at presentation. AJNR Am J Neuroradiol 2000; 21; 6: 1034-8. 116. Castriota Scanderbeg A, Tomaiuolo F, Sabatini U, Nocentini U, Grasso MG, Caltagirone C. Demyelinating plaques in relapsingremitting and secondary-progressive multiple sclerosis: assessment with diffusion MR imaging. AJNR Am J Neuroradiol 2000; 21; 5: 862-8. 102. Brex PA, Leary SM, Plant GT, Thompson AJ, Miller DH. Magnetization transfer imaging in patients with clinically isolated syndromes suggestive of multiple sclerosis. AJNR Am J Neuroradiol 2001; 22; 5: 947-51. 117. Nusbaum AO, Tang CY, Wei T, Buchsbaum MS, Atlas SW. Whole-brain diffusion MR histograms differ between MS subtypes. Neurology 2000; 54; 7: 1421-7. 103. Cercignani M, Horsfield MA. The physical basis of diffusionweighted MRI. J Neurol Sci 2001; 186; Suppl 1: S11-4. 104. Beaulieu C, Allen PS. Water diffusion in the giant axon of the squid: implications for diffusion-weighted MRI of the nervous system. Magn Reson Med 1994; 32; 5: 579-83. 105. Schaefer PW, Grant PE, Gonzalez RG. Diffusion-weighted MR imaging of the brain. Radiology 2000; 217; 2: 331-45. 118. Roychowdhury S, Maldjian JA, Grossman RI. Multiple sclerosis: comparison of trace apparent diffusion coefficients with MR enhancement pattern of lesions. AJNR Am J Neuroradiol 2000; 21; 5: 869-74. 119. Cercignani M, Iannucci G, Rocca MA, Comi G, Horsfield MA, Filippi M. Pathologic damage in MS assessed by diffusionweighted and magnetization transfer MRI. Neurology 2000; 54; 5: 1139-44. Page 15 of 18 120. Hagberg G, Valancherry J, Fasano F, Nocentini U, Sabatini U, Sanes J, Castriota-Scanderbeg A. Co-localization of changes in ADC, T1 -relaxation time and 1 H-metabolite concentrations in MS-lesions. Proc Int Soc Magn Reson Med 2001; 9: 153. (Abstr.) 121. Rocca MA, Cercignani M, Iannucci G, Comi G, Filippi M. Weekly diffusion-weighted imaging of normal-appearing white matter in MS. Neurology 2000; 55; 6: 882-4. spectra of active and chronic multiple sclerosis lesions. Magn Reson Med 2000; 43; 1: 102-10. 135. Sarchielli P, Presciutti O, Pelliccioli GP, Tarducci R, Gobbi G, Chiarini P, Alberti A, Vicinanza F, Gallai V. Absolute quantification of brain metabolites by proton magnetic resonance spectroscopy in normal-appearing white matter of multiple sclerosis patients. Brain 1999; 122; Pt 3: 513-21. 122. De Stefano N, Narayanan S, Matthews PM, Francis GS, Antel JP, Arnold DL. In vivo evidence for axonal dysfunction remote from focal cerebral demyelination of the type seen in multiple sclerosis. Brain 1999; 122; Pt 10: 1933-9. 136. van Walderveen MA, Barkhof F, Pouwels PJ, van Schijndel RA, Polman CH, Castelijns JA. Neuronal damage in T1-hypointense multiple sclerosis lesions demonstrated in vivo using proton magnetic resonance spectroscopy. Ann Neurol 1999; 46; 1: 7987. 123. Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B 1996; 111; 3: 209-19. 137. Provencher SW. Estimation of metabolite concentrations from localized in vivo proton NMR spectra. Magn Reson Med 1993; 30; 6: 672-9. 124. Pierpaoli C, Basser PJ. Toward a quantitative assessment of diffusion anisotropy. Magn Reson Med 1996; 36; 6: 893-906. 138. Pan JW, Twieg DB, Hetherington HP. Quantitative spectroscopic imaging of the human brain. Magn Reson Med 1998; 40; 3: 363-9. 125. Shimony JS, McKinstry RC, Akbudak E, Aronovitz JA, Snyder AZ, Lori NF, Cull TS, Conturo TE. Quantitative diffusion-tensor anisotropy brain MR imaging: normative human data and anatomic analysis. Radiology 1999; 212; 3: 770-84. 126. Bammer R, Augustin M, Strasser-Fuchs S, Seifert T, Kapeller P, Stollberger R, Ebner F, Hartung HP, Fazekas F. Magnetic resonance diffusion tensor imaging for characterizing diffuse and focal white matter abnormalities in multiple sclerosis. Magn Reson Med 2000; 44; 4: 583-91. 127. Werring DJ, Clark CA, Barker GJ, Thompson AJ, Miller DH. Diffusion tensor imaging of lesions and normal-appearing white matter in multiple sclerosis. Neurology 1999; 52; 8: 1626-32. 128. Iannucci G, Rovaris M, Giacomotti L, Comi G, Filippi M. Correlation of multiple sclerosis measures derived from T2weighted, T1-weighted, magnetization transfer, and diffusion tensor MR imaging. AJNR Am J Neuroradiol 2001; 22; 8: 14627. 129. Guo AC, Jewells VL, Provenzale JM. Analysis of normalappearing white matter in multiple sclerosis: comparison of diffusion tensor MR imaging and magnetization transfer imaging. AJNR Am J Neuroradiol 2001; 22; 10: 1893-900. 130. Griffin CM, Chard DT, Ciccarelli O, Kapoor B, Barker GJ, Thompson AI, Miller DH. Diffusion tensor imaging in early relapsing-remitting multiple sclerosis. Mult Scler 2001; 7; 5: 290-7. 131. Arnold DL, De Stefano N, Narayanan S, Matthews PM. Proton MR spectroscopy in multiple sclerosis. Neuroimaging Clin N Am 2000; 10; 4: 789-798. 132. Ross B, Bluml S. Magnetic resonance spectroscopy of the human brain. Anat Rec (New Anat) 2001; 265; 54-84. 133. De Stefano N, Matthews PM, Antel JP, Preul M, Francis G, Arnold DL. Chemical pathology of acute demyelinating lesions and its correlation with disability. Ann Neurol 1995; 38; 6: 9019. 134. Helms G, Stawiarz L, Kivisakk P, Link H. Regression analysis of metabolite concentrations estimated from localized proton MR 139. Moffett JR, Namboodiri MA, Cangro CB, Neale JH. Immunohistochemical localization of N-acetylaspartate in rat brain. Neuroreport 1991; 2; 3: 131-4. 140. Simmons ML, Frondoza CG, Coyle JT. Immunocytochemical localization of N-acetyl-aspartate with monoclonal antibodies. Neuroscience 1991; 45; 1: 37-45. 141. Urenjak J, Williams SR, Gadian DG, Noble M. Specific expression of N-acetylaspartate in neurons, oligodendrocyte-type-2 astrocyte progenitors, and immature oligodendrocytes in vitro. J Neurochem 1992; 59; 1: 55-61. 142. Bhakoo KK, Pearce D. In vitro expression of N-acetyl aspartate by oligodendrocytes: implications for proton magnetic resonance spectroscopy signal in vivo. J Neurochem 2000; 74; 1: 254-62. 143. Bjartmar C, Battistuta J, Terada N, Dupree E, Trapp BD. Nacetylaspartate is an axon-specific marker of mature white matter in vivo: A biochemical and immunohistochemical study on the rat optic nerve. Ann Neurol 2002; 51; 1: 51-8. 144. Bitsch A, Bruhn H, Vougioukas V, Stringaris A, Lassmann H, Frahm J, Bruck W. Inflammatory CNS demyelination: histopathologic correlation with in vivo quantitative proton MR spectroscopy. AJNR Am J Neuroradiol 1999; 20; 9: 1619-27. 145. Bjartmar C, Kidd G, Mork S, Rudick R, Trapp BD. Neurological disability correlates with spinal cord axonal loss and reduced Nacetyl aspartate in chronic multiple sclerosis patients. Ann Neurol 2000; 48; 6: 893-901. 146. Arnold DL, Matthews PM, Francis G, Antel J. Proton magnetic resonance spectroscopy of human brain in vivo in the evaluation of multiple sclerosis: assessment of the load of disease. Magn Reson Med 1990; 14; 1: 154-9. 147. Matthews PM, Francis G, Antel J, Arnold DL. Proton magnetic resonance spectroscopy for metabolic characterization of plaques in multiple sclerosis. Neurology 1991; 41; 8: 1251-6. 148. Arnold DL, Matthews PM, Francis GS, O'Connor J, Antel JP. Proton magnetic resonance spectroscopic imaging for metabolic characterization of demyelinating plaques. Ann Neurol 1992; 31; 3: 235-41. Page 16 of 18 149. De Stefano N, Narayanan S, Francis GS, Arnaoutelis R, Tartaglia MC, Antel JP, Matthews PM, Arnold DL. Evidence of axonal damage in the early stages of multiple sclerosis and its relevance to disability. Arch Neurol 2001; 58; 1: 65-70. 150. Mainero C, De Stefano N, Iannucci G, Sormani MP, Guidi L, Federico A, Bartolozzi ML, Comi G, Filippi M. Correlates of MS disability assessed in vivo using aggregates of MR quantities. Neurology 2001; 56; 10: 1331-4. 151. Pan JW, Krupp LB, Elkins LE, Coyle PK. Cognitive dysfunction lateralizes with NAA in multiple sclerosis. Appl Neuropsychol 2001; 8; 3: 155-60. 152. Mader I, Roser W, Kappos L, Hagberg G, Seelig J, Radue EW, Steinbrich W. Serial proton MR spectroscopy of contrastenhancing multiple sclerosis plaques: absolute metabolic values over 2 years during a clinical pharmacological study. AJNR Am J Neuroradiol 2000; 21; 7: 1220-7. 153. Mader I, Seeger U, Weissert R, Klose U, Naegele T, Melms A, Grodd W. Proton MR spectroscopy with metabolite-nulling reveals elevated macromolecules in acute multiple sclerosis. Brain 2001; 124; Pt 5: 953-61. 163. Losseff NA, Webb SL, O'Riordan JI, Page R, Wang L, Barker GJ, Tofts PS, McDonald WI, Miller DH, Thompson AJ. Spinal cord atrophy and disability in multiple sclerosis. A new reproducible and sensitive MRI method with potential to monitor disease progression. Brain 1996; 119; Pt 3: 701-8. 164. Stevenson VL, Leary SM, Losseff NA, Parker GJ, Barker GJ, Husmani Y, Miller DH, Thompson AJ. Spinal cord atrophy and disability in MS: a longitudinal study. Neurology 1998; 51; 1: 234-8. 165. Nijeholt GJ, van Walderveen MA, Castelijns JA, van Waesberghe JH, Polman C, Scheltens P, Rosier PF, Jongen PJ, Barkhof F. Brain and spinal cord abnormalities in multiple sclerosis. Correlation between MRI parameters, clinical subtypes and symptoms. Brain 1998; 121; Pt 4: 687-97. 166. Lin X, Blumhardt LD. Inflammation and atrophy in multiple sclerosis: MRI associations with disease course. J Neurol Sci 2001; 189; 1-2: 99-104. 167. Filippi M, Colombo B, Rovaris M, Pereira C, Martinelli V, Comi G. A longitudinal magnetic resonance imaging study of the cervical cord in multiple sclerosis. J Neuroimaging 1997; 7; 2: 78-80. 154. Simone IL, Tortorella C, Federico F, Liguori M, Lucivero V, Giannini P, Carrara D, Bellacosa A, Livrea P. Axonal damage in multiple sclerosis plaques: a combined magnetic resonance imaging and 1H-magnetic resonance spectroscopy study. J Neurol Sci 2001; 182; 2: 143-50. 168. Huber SJ, Bornstein RA, Rammohan KW, Christy JA, Chakeres DW, McGhee RB. Magnetic resonance imaging correlates of neuropsychological impairment in multiple sclerosis. J Neuropsychiatry Clin Neurosci 1992; 4; 2: 152-8. 155. Ogawa S, Lee TM, Kay AR, Tank DW. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc Natl Acad Sci U S A 1990; 87; 24: 9868-72. 169. Clark CM, James G, Li D, Oger J, Paty D, Klonoff H. Ventricular size, cognitive function and depression in patients with multiple sclerosis. Can J Neurol Sci 1992; 19; 3: 352-6. 156. Reddy H, Narayanan S, Arnoutelis R, Jenkinson M, Antel J, Matthews PM, Arnold DL. Evidence for adaptive functional changes in the cerebral cortex with axonal injury from multiple sclerosis. Brain 2000; 123; Pt 11: 2314-20. 170. Comi G, Filippi M, Martinelli V, Sirabian G, Visciani A, Campi A, Mammi S, Rovaris M, Canal N. Brain magnetic resonance imaging correlates of cognitive impairment in multiple sclerosis. J Neurol Sci 1993; 115; Suppl: S66-73. 157. Rocca MA, Pagani E, Comi G, Filippi M. Brain adaptive changes following tissue damage in PPMS: a multiparametric study using fMRI, MTI and DTI. Proc Int Soc Magn Reson Med 2001; 9: 151. (Abstr.) 171. Dastidar P, Heinonen T, Lehtimaki T, Ukkonen M, Peltola J, Erila T, Laasonen E, Elovaara I. Volumes of brain atrophy and plaques correlated with neurological disability in secondary progressive multiple sclerosis. J Neurol Sci 1999; 165; 1: 36-42. 158. Rudick RA, Fisher E, Lee JC, Simon J, Jacobs L. Use of the brain parenchymal fraction to measure whole brain atrophy in relapsing-remitting MS. Multiple Sclerosis Collaborative Research Group. Neurology 1999; 53; 8: 1698-704. 172. Luks TL, Goodkin DE, Nelson SJ, Majumdar S, Bacchetti P, Portnoy D, Sloan R. A longitudinal study of ventricular volume in early relapsing-remitting multiple sclerosis. Mult Scler 2000; 6; 5: 332-7. 159. Collins LD, Narayanan S, Caramanos Z, De Stefano N, Tartaglia MC, Arnold DL. Relation of cerebral atrophy in multiple sclerosis to severity of disease and axonal injury. Neurology 2000; 54: A17. (Abstr.) 173. Zivadinov R, Sepcic J, Nasuelli D, De Masi R, Bragadin LM, Tommasi MA, Zambito-Marsala S, Moretti R, Bratina A, Ukmar M, Pozzi-Mucelli RS, Grop A, Cazzato G, Zorzon M. A longitudinal study of brain atrophy and cognitive disturbances in the early phase of relapsing-remitting multiple sclerosis. J Neurol Neurosurg Psychiatry 2001; 70; 6: 773-80. 160. Simon JH. Brain and spinal cord atrophy in multiple sclerosis: role as a surrogate measure of disease progression. CNS Drugs 2001; 15; 6: 427-36. 161. Brex PA, Jenkins R, Fox NC, Crum WR, O'Riordan JI, Plant GT, Miller DH. Detection of ventricular enlargement in patients at the earliest clinical stage of MS. Neurology 2000; 54; 8: 168991. 162. Liu C, Edwards S, Gong Q, Roberts N, Blumhardt LD. Three dimensional MRI estimates of brain and spinal cord atrophy in multiple sclerosis. J Neurol Neurosurg Psychiatry 1999; 66; 3: 323-30. 174. Filippi M, Mastronardo G, Rocca MA, Pereira C, Comi G. Quantitative volumetric analysis of brain magnetic resonance imaging from patients with multiple sclerosis. J Neurol Sci 1998; 158; 2: 148-53. 175. Ge Y, Grossman RI, Udupa JK, Babb JS, Nyul LG, Kolson DL. Brain atrophy in relapsing-remitting multiple sclerosis: fractional volumetric analysis of gray matter and white matter. Radiology 2001; 220; 3: 606-10. Page 17 of 18 176. Bakshi R, Czarnecki D, Shaikh ZA, Priore RL, Janardhan V, Kaliszky Z, Kinkel PR. Brain MRI lesions and atrophy are related to depression in multiple sclerosis. Neuroreport 2000; 11; 6: 1153-8. 177. Janardhan V, Bakshi R. Quality of life and its relationship to brain lesions and atrophy on magnetic resonance images in 60 patients with multiple sclerosis. Arch Neurol 2000; 57; 10: 1485-91. 178. Edwards SG, Liu C, Blumhardt LD. Cognitive correlates of supratentorial atrophy on MRI in multiple sclerosis. Acta Neurol Scand 2001; 104; 4: 214-23. 179. Fox NC, Jenkins R, Leary SM, Stevenson VL, Losseff NA, Crum WR, Harvey RJ, Rossor MN, Miller DH, Thompson AJ. Progressive cerebral atrophy in MS: a serial study using registered, volumetric MRI. Neurology 2000; 54; 4: 807-12. 180. Simon JH, Jacobs LD, Campion MK, Rudick RA, Cookfair DL, Herndon RM, Richert JR, Salazar AM, Fischer JS, Goodkin DE, Simonian N, Lajaunie M, Miller DE, Wende K, MartensDavidson A, Kinkel RP, Munschauer FE, 3rd, Brownscheidle CM. A longitudinal study of brain atrophy in relapsing multiple sclerosis. The Multiple Sclerosis Collaborative Research Group (MSCRG). Neurology 1999; 53; 1: 139-48. 181. Bakshi R, Benedict RH, Bermel RA, Jacobs L. Regional brain atrophy is associated with physical disability in multiple sclerosis: semiquantitative magnetic resonance imaging and relationship to clinical findings. J Neuroimaging 2001; 11; 2: 129-36. 182. Chen JT, Matthews PM, Arnold DL, Zhang Y, Smith SM. Regional brain atrophy in multiple sclerosis: increasing sensitivity to differences in relapsing-remitting and secondary-progressive disease. Proc Int Soc Magn Reson Med 2001; 9: 265. (Abstr.) 183. Paolillo A, Pozzilli C, Gasperini C, Giugni E, Mainero C, Giuliani S, Tomassini V, Millefiorini E, Bastianello S. Brain atrophy in relapsing-remitting multiple sclerosis: relationship with 'black holes', disease duration and clinical disability. J Neurol Sci 2000; 174; 2: 85-91. 184. Sailer M, Losseff NA, Wang L, Gawne-Cain ML, Thompson AJ, Miller DH. T1 lesion load and cerebral atrophy as a marker for clinical progression in patients with multiple sclerosis. A prospective 18 months follow-up study. Eur J Neurol 2001; 8; 1: 37-42. 185. Leist TP, Gobbini MI, Frank JA, McFarland HF. Enhancing magnetic resonance imaging lesions and cerebral atrophy in patients with relapsing multiple sclerosis. Arch Neurol 2001; 58; 1: 57-60. 186. Saindane AM, Ge Y, Udupa JK, Babb JS, Mannon LJ, Grossman RI. The effect of gadolinium-enhancing lesions on whole brain atrophy in relapsing-remitting MS. Neurology 2000; 55; 1: 61-5. Page 18 of 18