Share

April 23, 2002; 58 (8) Views & Reviews

MRI techniques to monitor MS evolution

The present and the future

Massimo Filippi, Robert I. Grossman
First published April 23, 2002, DOI: https://doi.org/10.1212/WNL.58.8.1147
Full PDF
Citation
Permissions

Make Comment

See Comments

Downloads
2021

Share

Abstract

Conventional MRI (cMRI) is limited in its ability to provide specific information about pathology in MS. Measures commonly derived from cMRI include T2 lesions, T1-enhanced lesions, atrophy, and possibly T1-hypointense lesions, which have been extensively investigated in many clinical trials. Better MRI measures are needed to advance our understanding of MS and design ideal clinical trials. This article reviews the strengths and weaknesses of the major MRI-based methods used to monitor MS evolution and submits that 1) metrics derived from magnetization transfer MRI, diffusion-weighted MRI, and proton MRS should be implemented to achieve reliable specific in vivo quantification of MS pathology; 2) targeted multiparametric MRI protocols rather than generic application of cMRI should be used in all possible clinical circumstances and trials; and 3) reproducible quantitative MR measures should ideally be used for the assessment of patients but are essential for clinical trials.

There have been impressive advances in the implementation of MRI for the assessment of patients with MS. Conventional MRI (cMRI) (i.e., dual-echo T2-weighted and postcontrast T1-weighted scans) has become established not only as the most important paraclinical tool for diagnosing MS1 but also for understanding its natural history and monitoring the efficacy of experimental treatments.2 However, the correlation found between the extent of lesions observed on cMRI and the clinical manifestations of the disease is weak.3,4⇓ The discrepancy between clinical MRI and cMRI in MS is explained, in part, by the limited ability of cMRI to characterize and quantify the features of pathology in MS.

What is measured when using conventional MRI?

Hyperintense lesions on dual-echo MRI provide a nonspecific measure of the overall extent of macroscopic tissue injury. Increased signal intensity on these scans in large measure reflects increased tissue water. The abnormal tissue water may be associated with different pathologic substrates, ranging from edema and inflammation to irreversible demyelination and axonal loss and, consequently, could represent different clinical outcomes. Enhancing abnormalities on T1-weighted images are those lesions with blood–brain barrier permeability that allows large enough gadolinium leakage to be detected visually. However, the detection of enhancing lesions provides no information about the extent and severity of the inflammatory phase,5,6⇓ the constitution of its cellular components,7,8⇓ or the resultant tissue damage.9,10⇓

What else should ideally be measured using MR-based technology?

In addition to the extent of macroscopic white matter abnormalities, the following aspects of MS pathology are likely to be important in determining patients’ functional impairment and, ideally, should be measured using MR-based technology.

The cellular component of MS inflammation.

Vascular adhesion and transvascular trafficking of mononuclear cells are necessary prerequisites in the pathogenesis of new lesions and likely to be important contributors to subsequent lesion evolution.7,8⇓

The pathologic substrate of lesions visible on cMRI.

The extent of reversible and irreversible tissue injury is variable and will be likely to impact the clinical outcome.11

The magnitude and severity of tissue damage in normal-appearing white matter (NAWM).

Postmortem studies have shown several histopathologic abnormalities in the NAWM of patients with MS, including loss of axons.12,13⇓ NAWM represents a large portion of the brain tissue even in patients with high T2 lesion volumes. Consistent with these observations, several studies have shown that abnormalities in the NAWM are one factor, if not the most important, contributing to neurologic impairment.14-16⇓⇓

The extent of gray matter pathology.

MS does not spare cerebral gray matter.17,18⇓ A working hypothesis is that the degree of cerebral gray matter damage is likely to contribute to the development of at least some of the clinical deficits in MS, such as cognitive impairment, mood disorders, and fatigue.

The extent of disease in the spinal cord and the optic nerve.

Despite having a propensity for MS lesions, the optic nerves and spinal cord have been suboptimally evaluated, in part due to technical considerations. Recent work has shown that it is possible to obtain reliable quantitation of spinal cord19,20⇓ and optic nerve21-23⇓⇓ lesions and that, as expected, the extent of such damage is correlated with the degree of functional impairment.24 Interestingly, damage in the cervical cord is only marginally related to that in the brain,25 indicating that quantitative imaging of (at least) the cervical cord can provide information about the disease process complementary to that achievable with brain MRI alone.

The effectiveness of repair after tissue injury.

Reparative mechanisms in MS include removal of inflammatory mediators, resolution of edema, remyelination, redistribution of voltage-gated sodium channels, reactive gliosis, recovery from sublethal axonal injury, and cortical adaptive reorganization. Although our ability to monitor these processes using MR is still limited, it is certain that such a goal would represent a major achievement in our understanding of the disease and the assessment of treatment efficacy.

What are the minimum requisites for an MRI-derived measure to be used in the monitoring of MS?

Against this background and, in addition to the basic requisites that any paraclinical measure must meet before it can be applied routinely in clinical medicine (i.e., accuracy, reproducibility, sensitivity to change, cost efficiency, and clinical meaningfulness), the following are suggested as additional requisites for MRI-derived measures to be used to monitor MS evolution.

First, the measures must be quantitative. Given the high variability of the severity of MS pathology between patients and between lesions and abnormalities in the NAWM of the same patients,4,11⇓ it is important to have quantitative measures to grade precisely the extent of tissue damage.

Second, the measures should provide information about (at least) the entire pathologic range of the disease, but especially irreversible tissue loss, an increasingly important aspect of MS.26 Data are emerging that axonal loss is a major factor in causing MS irreversible disability.27

Finally, the measures must examine the entire brain. MS is a widespread disease affecting all the CNS tissues.28 Consequently, MRI measures should be able to reflect disease pathology of the entire CNS. Ideally, it should be possible to extract from the global measures information regarding specific anatomic regions.

What is currently used?

T1-hypointensity. Hypointense lesions on enhanced T1-weighted images (known as “black holes”) have been reported to correspond to areas where chronic severe tissue disruption has occurred.29 Although strong correlation was initially described between the T1-hypointense lesion volume and disability,30 this has not been confirmed by later studies based on much larger samples of patients.31,32⇓ This approach also has major limitations when used to monitor MS evolution.

First, defining what constitutes a “black hole” is arbitrary and highly operator dependent. The first step in measuring T1-hypointense lesion volumes is the identification of individual “black holes.” This is usually a binary classification (“it is a black hole” or “it is not a black hole”) based on visual inspection of an experienced reader, which in turn depends on the MR scanner performance and the acquisition parameters used. Thus, T1-hypointense volume measurements do not provide graded information about intrinsic pathology of individual lesions. In vivo quantitative MRI and MRS33,34⇓ reveal that tissue damage is extremely variable in individual “black holes.”

Second, T1-hypointense lesion volume assessment does not provide any information about pathology of NAWM. “Black holes” are difficult to detect in areas critical for the accumulation of irreversible MS disability, such as the brainstem, the spinal cord, and the optic nerve.35

Finally, there is direct evidence from postmortem studies36,37⇓ confirming the variability of the pathology, thus greatly reducing the specificity and appeal of the measure.

Brain atrophy.

Measurement of atrophy (particularly of the brain and the cervical cord) has been applied to assess the extent of tissue loss in MS.38-40⇓⇓ This MRI-derived measure is also not without problems.

First, the pathologic basis of MS-related atrophy is still unclear. Although it is intuitive that myelin and axonal loss might contribute to the development of atrophy, the role of other factors is largely unexplored. For instance, reactive gliosis has the potential to mask considerable tissue loss. Measurements of brain atrophy are also likely to be biased by fluctuations of tissue water content related to important aspects of MS pathology or management, such as the vasogenic edema coupled to active lesions or the administration of “anti-inflammatory” treatment.

Second, atrophy is an end-stage phenomenon. Although detection of atrophy is a hard endpoint, it is conceivable that a series of events (e.g., progressive myelin loss, inefficient remyelination, sublethal axonal injury) would precede MRI-detectable atrophy. The ability to monitor the process prior to irreversibility is more desirable than measuring the end result of the process (atrophy); i.e., brain atrophy should be viewed as an outcome measure rather than as a tool to monitor ongoing pathology.

Finally, atrophy is relatively insensitive to disease changes. On average, brain volume decreases by about 1% yearly in patients with different MS phenotypes.40-44⇓⇓⇓⇓ This indicates that large patient samples and long follow-up periods might be needed to detect treatment effect on the rate of atrophy development.

What else should be used?

There is a compelling need to define more sensitive and more specific MRI measures for use in the monitoring of MS. At present, none of the available MR techniques is able to provide metrics that fulfill the requisites for being considered the dominant surrogate of MS pathology. Nevertheless, the following quantitative MR techniques hold substantial promise:

Magnetization transfer MRI.

Magnetization transfer MRI (MT-MRI) is based on the interactions between protons in a relatively free environment and those where motion is restricted. In the CNS, these two states correspond to the protons in tissue water and in the macromolecules of myelin and other cell membranes. Off-resonance irradiation is applied, which saturates the magnetization of the less mobile protons, but this is transferred to the mobile protons, thus reducing the signal intensity from the observable magnetization. The degree of signal loss depends on the density of the macromolecules in a given tissue. Thus, low MT ratio (MTR) indicates a reduced capacity of the macromolecules in the CNS to exchange magnetization with the surrounding water molecules, likely reflecting loss of myelin and reduction in axonal density.

  1. Pros:

  2. • MTR is a quantitative and continuous measure.

  3. • Although MTR decreases are not specific to any of the various MS pathologic substrates,45 human postmortem46 and experimental animal47-49⇓⇓ studies indicate a strict relation between MTR and the percentage of residual axons and the degree of demyelination.

  4. • MTR analysis can provide information about tissue injury to the entire brain,50,51⇓ to specific CNS structures, such as the cerebrum,52,53⇓ the infratentorial brain,54 the cervical cord,24 and the optic nerve22,23⇓ and to specific tissues, i.e., macroscopic lesions,44,55⇓ normal-appearing brain tissue,15 NAWM,56,57⇓ and gray matter.56,57⇓ Serial MTR studies have the potential to monitor reparative mechanisms, such as demyelination.58-61⇓⇓⇓

  5. • Quantities derived from MT-MRI are reproducible,62 sensitive to disease changes over 1 year,44 and relatively cost-effective (high-quality MTR data can be obtained with scanning time of <10 minutes).

  6. • Quantities derived from MT-MRI are correlated with the degree of disability15,24,51⇓⇓ and cognitive impairment.16

  1. Cons:

  2. • Clinical applications of MT measurements are based on a two-site exchange model. More complex models, with the potential to improve the characterization of tissue structure, are available, but to date their application to MS monitoring is limited.63

  3. • MTR analysis must be coupled with the acquisition of cMRI if there is a desire for correlation with specific MR parameters (enhancement, T2 lesion load, and so on).

  4. • MTR is dependent on scanner characteristics and acquisition parameters. Although it is possible,64 optimization and standardization across multiple sites and over time of MT sequence can be challenging.65

  5. • There are no long-term longitudinal studies using MTR. Consequently, the predictive value of MTR changes is unknown.

Diffusion-weighted MRI.

Diffusion is the random translational motion of molecules in a fluid system. In the CNS, diffusion is influenced by the microstructural components of tissue, including cell membranes and organelles. Water molecular diffusion can be measured in vivo using MRI and, consequently, diffusion-weighted MRI (DW-MRI) is sensitive to pathologic processes that, by modifying tissue integrity, result in loss or increased permeability of “restricting” barriers to water molecular motion and in a loss of tissue anisotropy. Thus, measures derived from DW-MRI can give information about the size, shape, geometry, and orientation of tissues.

  1. Pros:

  2. • Measures derived from DW-MRI are quantitative and continuous. Although DW-MRI changes are not likely to reflect specific pathologic substrates, the demonstration of abnormal water diffusivity in the cortical gray matter and in the white matter of patients with AD66-68⇓⇓ suggests that neuronal and axonal loss are relevant contributors.

  3. • Analysis of DW-MRI can assess the entire brain69 or a large portion of it70 as well as specific brain regions.56,57⇓ Although DW-MRI of the optic nerve and spinal cord present considerable technical challenge, successful DW-MRI of these CNS regions have been recently obtained.20,21⇓

  4. • Significant cross-sectional correlations between DW-MRI findings and MS clinical manifestations and disability are emerging.35,69,71,72⇓⇓⇓

  1. Cons:

  2. • As with MTR, DW-MRI analysis must be coupled with the acquisition of cMRI if correlations with MR parameters are required. Optimization and standardization across multiple sites and over time of DW-MRI is likely to be challenging.73

  3. • Currently, the reproducibility and the sensitivity to changes of DW-MRI quantities are unknown. Also, there are no long-term longitudinal studies using DW-MRI. Consequently, the magnitude of the correlation between DW-MRI and disability changes, and the predictive value of DW MRI findings, are unknown.

Proton MRS (1H-MRS).

Water-suppressed, proton MR spectra of normal human brain at long echo times reveal four major resonances: one at 3.2 ppm from tetramethylamines (mainly from choline-containing phospholipids), one at 3.0 ppm from creatine and phosphocreatine, one at 2.0 ppm from N-acetyl groups (mainly N-acetylaspartate, and one at 1.3 ppm from the methyl resonance of lactate. Although more technically demanding, additional metabolites (including lipids and myoinositol) can be detected using short-echo-time measurements.

  1. Pros:

  2. • 1H-MRS provides quantitative and continuous measures. 1H-MRS can provide quantitative information about two of the major pathologic aspects of MS, i.e., the active inflammatory/demyelinating process and axonal injury.27,74⇓ Active demyelination produces changes in the resonances from choline (reflecting myelin breakdown and release of membrane phospholipids containing choline). Lactate increases with inflammation due to anaerobic metabolism of inflammatory cells, associated mitochondrial dysfunction, and, in severe cases, occlusion of microvessels. Lipids, which are normally present in membranes but not visible in MR spectra due to restricted mobility, produce observable resonances as their mobility increases and as they are released from membranes. Axonal injury and loss can be quantified through the measurement of changes in the intensity of N-acetylaspartate. Because N-acetylaspartate is localized essentially exclusively in neurons and neuronal processes (dendrites and axons) in the normal mature brain,75 reductions in the resonance intensity of N-acetylaspartate in the white matter of patients with MS reflect changes in axonal density, size, or metabolism.27,74⇓

  3. • 1H-MRS can provide information about tissue injury in a large segment of brain tissue. This can be achieved by placing a large voxel in the central brain.76-78⇓⇓ More recently, successful whole brain N-acetylaspartate measurements have also been achieved.79

  4. • Quantities derived from 1H-MRS are sensitive to disease changes over time.78,80⇓

  5. • Quantities derived from 1H-MRS are correlated with disability.14,77,78,80,81⇓⇓⇓⇓

  1. Cons:

  2. 1H-MRS studies are relatively time consuming and require, for their acquisition, postprocessing, and interpretation, information from cMR images as well as knowledgeable and experienced personnel. Consequently, high-quality 1H-MRS technology and operators are still confined to relatively few centers.

  3. 1H-MRS generally provides a relatively low signal-to-noise ratio due to the low concentration of metabolites in tissues. To obtain adequate signal-to-noise ratio, relatively large voxel sizes are required. This predisposes to partial volume effects when studying focal pathology such as MS lesions. In addition, there is generally a selection of lesions or NAWM areas to be studied, with the possibility of sampling and repositioning errors in serial studies. This inevitably reduces the reproducibility of 1H-MRS measures. The use of whole brain N-acetylaspartate measurements overcomes these limitations but does not enable us to obtain information about pathology of specific brain regions or tissues.79

  4. Quantification of 1H-MRS spectra has often relied on the ratio of N-acetylaspartate to another metabolite (especially creatine) rather than on absolute measurements. This is a major issue when considering that pathology may change the concentration of the reference metabolites.82,83⇓ However, recent technical improvements allow the measurement of absolute N-acetylaspartate concentration from individual voxels of a single slice84 or from the whole brain.79

  5. Optimization and standardization across multiple sites and over time of 1H-MRS is challenging.85

The future is now?

The MRI techniques described here have largely been applied to the in vivo assessment of MS pathology and, in the near future, are likely to enter a phase of more widespread routine clinical practice and to be used (at least as exploratory endpoints) in large-scale clinical trials of MS. Other techniques and approaches, however, are receiving increasing attention from the MS/MRI research community that, although of limited availability, deserve to be mentioned.

Cell-specific imaging.

A superparamagnetic iron oxide contrast agent, also known as monocrystalline iron oxide nanoparticles (MION), can be used to label various cell components of the immune system for in vivo trafficking studies.7,8⇓ MION-enhanced MRI shows a higher sensitivity for the detection of experimental allergic encephalomyelitis lesions than that of conventional T2-weighted and gadolinium-enhanced images.7,8⇓ Histopathologic analysis has revealed the presence of macrophages at the sites where MION-enhanced abnormalities were seen.8 Preliminary data in patients with MS have shown that there is a relatively large group of “active” MS lesions that enhance only after either MION or gadolinium injection (V. Dousset, personal communication). Understanding this “active” MS lesion heterogeneity might improve our understanding of the disease pathobiology.

fMRI.

fMRI aids in the mapping of regions of brain activation during motor, sensitive, and cognitive tasks and can define changes in brain activation associated with disease. fMRI quantitates the blood oxygenation level–dependent effect and detects areas of the brain that have greater local blood flow, reflecting increased neuronal activity during task performance compared with rest. Recent fMRI work has provided evidence for adaptive cortical reorganization with the potential to limit the clinical consequences of MS tissue injury in several disease phenotypes.86-89⇓⇓⇓

High field strengths.

The use of high field strengths leads to improved signal-to-noise ratio, speed, and resolution in both MRI and MRS. 3-T MR has already been approved by the Food and Drug Administration and higher-field MR is moving rapidly. Although the safety of field strengths >3 Tesla has not been established, no doubt higher-field imaging will affect anatomic visualization, proton and nonproton MRS, fMRI, and nonproton imaging (sodium).

Conclusions

  • Although cMRI has improved our understanding of MS and treatment, it provides limited information about MS pathology in terms of both accuracy and specificity. This has at least two major consequences. First, cMRI findings should not be used to establish prognosis for individual patients with MS (treated or untreated). Second, the ability of a given treatment to modify metrics derived from cMRI does not mean necessarily that the treatment will be able to favorably modify the disease course.

  • There is an urgent need to define MRI markers of MS evolution, which should be quantitative and should provide information about the most destructive aspects of MS pathology and of the entire brain. This is particularly compelling now that there is partially effective treatment for MS, and the ability to conduct large placebo-controlled trials is therefore limited.90

  • Metrics derived from MT-MRI, DW-MRI, and 1H-MRS should be increasingly used to monitor MS evolution, either natural or modified by treatment. At present, longitudinal natural history data collected in large samples of patients using these MR techniques are needed to gain additional insights into disease pathophysiology and into the value of these techniques in the assessment of MS.

  • It is the responsibility of the neuroimaging research community to advance the application of quantitative MRI for the assessment of patients with MS, especially in the context of clinical trials. None of the available MRI techniques is able to provide a complete picture of the complexity of the MS process. Although few data are available on composite MRI scores,91,92⇓ this should call for the definition of aggregates of MRI quantities thought to reflect different aspects of MS pathology to improve our ability to monitor the disease. The variability of the disease process in the different MS phases and phenotypes, as well as the heterogeneity of the mechanisms of action of the proposed therapies, should lead to the design of specific MRI protocols rather than to a generic application of cMRI metrics in all possible contexts.

Acknowledgments

Acknowledgment

The authors thank Dr. Mark A. Horsfield for thoughtful discussion.

  • Received August 16, 2001.
  • Accepted November 30, 2001.

References

  1. ↵
    McDonald WI, Compston A, Edan G, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the international panel on the diagnosis of multiple sclerosis. Ann Neurol . 2001; 50: 121–127.
    OpenUrlCrossRefPubMed
  2. ↵
    Filippi M, Horsfield MA, Ader HJ, et al. Guidelines for using quantitative measures of brain magnetic resonance imaging abnormalities in monitoring the treatment of multiple sclerosis. Ann Neurol . 1998; 43: 499–506.
    OpenUrlCrossRefPubMed
  3. ↵
    Kappos L, Moeri D, Radü EW, et al. Predictive value of gadolinium-enhanced MRI for relapse rate and changes in disability or impairment in multiple sclerosis: a meta-analysis. Lancet . 1999; 353: 964–969.
    OpenUrlCrossRefPubMed
  4. ↵
    Filippi M. Linking structural, metabolic and functional changes in multiple sclerosis. Eur J Neurol . 2001; 8: 291–297.
    OpenUrlCrossRefPubMed
  5. ↵
    Tofts PS. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J Magn Reson Imaging . 1997; 7: 91–101.
    OpenUrlCrossRefPubMed
  6. ↵
    Katz D, Taubenberger JK, Cannella B, McFarlin DE, Raine CS, McFarland HF. Correlation between magnetic resonance imaging findings and lesion development in chronic, active multiple sclerosis. Ann Neurol . 1993; 34: 661–669.
    OpenUrlCrossRefPubMed
  7. ↵
    Dousset V, Delalande C, Ballarino L, et al. In vivo macrophage activity imaging in the central nervous system detected by magnetic resonance. Magn Reson Med . 1999; 41: 329–333.
    OpenUrlCrossRefPubMed
  8. ↵
    Dousset V, Ballarino L, Delalande C, et al. Comparison of ultrasmall particles of iron oxide (USPIO)-enhanced T2-weighted, conventional T2-weighted and gadolinium-enhanced T1-weighted MR images in rats with experimental autoimmune encephalomyelitis. AJNR Am J Neuroradiol . 1999; 20: 223–227.
    OpenUrlAbstract/FREE Full Text
  9. ↵
    Filippi M, Rocca MA, Rizzo G, et al. Magnetization transfer ratios in multiple sclerosis lesions enhancing after different doses of gadolinium. Neurology . 1998; 50: 1289–1293.
    OpenUrlAbstract/FREE Full Text
  10. ↵
    Filippi M, Rocca MA, Comi G. Magnetization transfer ratios of multiple sclerosis lesions with variable durations of enhancement. J Neurol Sci . 1998; 159: 162–165.
    OpenUrlCrossRefPubMed
  11. ↵
    Filippi M. Magnetization transfer imaging to monitor the evolution of individual multiple sclerosis lesions. Neurology . 1999; 53 (suppl 3): S18–S22.
  12. ↵
    Trapp BD, Peterson J, Ransohoff RM, Rudick R, Mörk S, Bö L. Axonal transection in the lesions of multiple sclerosis. N Engl J Med . 1998; 338: 278–285.
    OpenUrlCrossRefPubMed
  13. ↵
    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: 1845–1849.
    OpenUrlAbstract/FREE Full Text
  14. ↵
    Fu L, Matthews PM, De Stefano N, et al. Imaging of axonal damage of normal appearing white matter in multiple sclerosis. Brain . 1998; 121: 103–113.
    OpenUrlAbstract/FREE Full Text
  15. ↵
    Tortorella C, Viti B, Bozzali M, et al. A magnetization transfer histogram study of normal appearing brain tissue in multiple sclerosis. Neurology . 2000; 54: 186–193.
    OpenUrlAbstract/FREE Full Text
  16. ↵
    Filippi M, Tortorella C, Rovaris M, et al. Changes in the normal-appearing brain tissue and cognitive impairment in multiple sclerosis. J Neurol Neurosurg Psychiatry . 2000; 68: 157–161.
    OpenUrlAbstract/FREE Full Text
  17. ↵
    Kidd D, Barkhof F, McConnel R, Algra PR, Allen IV, Revesz T. Cortical lesions in multiple sclerosis. Brain . 1999; 122: 17–26.
    OpenUrlAbstract/FREE Full Text
  18. ↵
    Peterson JW, Bö L, Mörk S, Chang A, Trapp BD. Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Ann Neurol . 2001; 50: 389–400.
    OpenUrlCrossRefPubMed
  19. ↵
    Bozzali M, Rocca MA, Iannucci G, Pereira C, Comi G, Filippi M. Magnetization transfer histogram analysis of the cervical cord in patients with multiple sclerosis. AJNR Am J Neuroradiol . 1999; 20: 1803–1808.
    OpenUrlAbstract/FREE Full Text
  20. ↵
    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: 133–138.
    OpenUrlCrossRefPubMed
  21. ↵
    Iwasawa T, Matoba H, Ogi A, et al. Diffusion-weighted imaging of the human optic nerve: a new approach to evaluate optic neuritis in multiple sclerosis. Magn Reson Med . 1997; 38: 484–491.
    OpenUrlPubMed
  22. ↵
    Thorpe JW, Barker GJ, Jones SJ, et al. Magnetisation transfer ratios and transverse magnetisation decay curves in optic neuritis: correlation with clinical findings and electrophysiology. J Neurol Neurosurg Psychiatry . 1995; 58: 487–492.
    OpenUrlAbstract/FREE Full Text
  23. ↵
    Inglese M, Rovaris M, Bianchi S, et al. Magnetic resonance imaging, magnetisation transfer imaging and diffusion weighted imaging correlates of optic nerve, brain and cervical cord damage in Leber’s hereditary optic neuropathy. J Neurol Neurosurg Psychiatry . 2001; 70: 444–449.
    OpenUrlAbstract/FREE Full Text
  24. ↵
    Filippi M, Bozzali M, Horsfield MA, et al. A conventional and magnetization transfer MRI study of the cervical cord in patients with multiple sclerosis. Neurology . 2000; 54: 207–213.
    OpenUrlAbstract/FREE Full Text
  25. ↵
    Rovaris M, Bozzali M, Santuccio G, et al. Relative contributions of brain and cervical cord pathology to MS disability: a study with MTR histogram analysis. J Neurol Neurosurg Psychiatry . 2000; 69: 723–727.
    OpenUrlAbstract/FREE Full Text
  26. ↵
    Rieckmann P, Smith KJ. Multiple sclerosis: more than inflammation and demyelination. Trends Neurosci . 2001; 24: 435–437.
    OpenUrlCrossRefPubMed
  27. ↵
    Arnold DL, De Stefano N, Narayanan S, Matthews PM. Axonal injury and disability in multiple sclerosis: magnetic resonance spectroscopy as a measure of dynamic pathological change in white matter. In: Filippi M, Arnold DL, Comi G, eds. Magnetic resonance spectroscopy in multiple sclerosis. Berlin-Heidelberg-New York: Springer Verlag, 2000: 61–67.
  28. ↵
    Filippi M. Multiple sclerosis: a white matter disease with associated gray matter damage. J Neurol Sci . 2001; 185: 3–4.
    OpenUrlCrossRefPubMed
  29. ↵
    van Walderveen MAA, Kamphorst W, Scheltens PH, et al. Histopathologic correlate of hypointense lesions on T1-weighted spin-echo MRI in multiple sclerosis. Neurology . 1998; 50: 1282–1288.
    OpenUrlAbstract/FREE Full Text
  30. ↵
    Truyen L, van Waesberghe JHTM, van Walderveen MAA, et al. Accumulation of hypointense lesions (“black holes”) on T1 spin-echo MRI correlates with disease progression in multiple sclerosis. Neurology . 1996; 47: 1469–1476.
    OpenUrlAbstract/FREE Full Text
  31. ↵
    Simon JH, Lull J, Jacobs LD, et al. A longitudinal study of T1 hypointense lesions in relapsing MS: MSCRG trial of interferon beta-1a. Multiple Sclerosis Collaborative Research Group. Neurology . 2000; 55: 185–192.
    OpenUrlAbstract/FREE Full Text
  32. ↵
    van Walderveen MA, Lycklama A, Nijeholt GJ, Ader HJ, et al. Hypointense lesions on T1-weighted spin-echo magnetic resonance imaging: relation to clinical characteristics in subgroups of patients with multiple sclerosis. Arch Neurol . 2001; 58: 76–81.
    OpenUrlCrossRefPubMed
  33. ↵
    Filippi M, Cercignani M, Inglese M, Horsfield MA, Comi G. Diffusion tensor magnetic resonance imaging in multiple sclerosis. Neurology . 2001; 56: 304–311.
    OpenUrlAbstract/FREE Full Text
  34. ↵
    Li BSY, Moriarty DM, Regal J, Mannon LJ, Grossman RI, Gonen O. In vivo 3D 1H MRS of T1-hypointense lesions in relapsing-remitting multiple sclerosis. Proc Int Soc Magn Reson Med . 2001; 9: 470.Abstract.
    OpenUrl
  35. ↵
    Gass A, Filippi M, Rodegher M, Schwartz A, Comi G, Hennerici MG. Characteristics of chronic MS lesions in the cerebrum, brain stem, spinal cord and optic nerve on T1-weighted MRI. Neurology . 1998; 50: 548–550.
    OpenUrlAbstract/FREE Full Text
  36. ↵
    Brück W, Bitsch A, Kolenda H, Brück Y, Stiefel M, Lassmann H. Inflammatory central nervous system demyelination: correlation of magnetic resonance imaging findings with lesion pathology. Ann Neurol . 1997; 42: 783–793.
    OpenUrlCrossRefPubMed
  37. ↵
    Bitsch A, Kuhlmann T, Stadelmann C, Lassmann H, Lucchinetti C, Bruck W. A longitudinal MRI study of histopathologically defined hypointense multiple sclerosis lesions. Ann Neurol . 2001; 49: 793–796.
    OpenUrlCrossRefPubMed
  38. ↵
    Losseff NA, Wang L, Lai HM, et al. Progressive cerebral atrophy in multiple sclerosis: a serial MRI study. Brain . 1996; 119: 2009–2019.
    OpenUrlAbstract/FREE Full Text
  39. ↵
    Losseff NA, Webb SL, O’Riordan J, et al. Spinal cord atrophy and disability in multiple sclerosis: a new reproducible and sensitive MRI method with potential to monitor disease progression. Brain . 1996; 119: 701–708.
    OpenUrlAbstract/FREE Full Text
  40. ↵
    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. Neurology . 1999; 53: 1698–1704.
    OpenUrlAbstract/FREE Full Text
  41. ↵
    Rovaris M, Comi G, Rocca MA, Wolinsky JS, Filippi M, European/Canadian Glatiramer Acetate Study Group. Short term brain volume change in relapsing-remitting multiple sclerosis: effect of glatiramer acetate and implications. Brain . 2001; 124: 1803–1812.
    OpenUrlAbstract/FREE Full Text
  42. ↵
    Filippi M, Rovaris M, Iannucci G, Mennea S, Sormani MP, Comi G. Whole brain volume changes in progressive MS patients treated with cladribine. Neurology . 2000; 55: 1714–1718.
    OpenUrlAbstract/FREE Full Text
  43. ↵
    Thompson AJ, Kermode AG, MacManus DG, et al. Patterns of disease activity in multiple sclerosis: clinical and magnetic resonance imaging study. BMJ . 1990; 300: 631–634.
  44. ↵
    Filippi M, Inglese M, Rovaris M, et al. Magnetization transfer imaging to monitor the evolution of MS: a 1-year follow up study. Neurology . 2000; 55: 940–946.
    OpenUrlAbstract/FREE Full Text
  45. ↵
    Gareau PJ, Rutt BK, Karlik SJ, Mitchell ZR. Magnetization transfer and multicomponent T2 relaxation measurements with histopathologic correlation in an experimental model of MS. J Magn Reson Imaging . 2000; 11: 586–595.
    OpenUrlCrossRefPubMed
  46. ↵
    van Waesberghe JH, Kamphorst W, De Groot CJ, et al. Axonal loss in multiple sclerosis lesions: magnetic resonance imaging insights into substrates of disability. Ann Neurol . 1999; 46: 747–754.
    OpenUrlCrossRefPubMed
  47. ↵
    Lexa FJ, Grossman RI, Rosenquist AC. MR of Wallerian degeneration in the feline visual system: characterization by magnetization transfer rate with histopathologic correlation. AJNR Am J Neuroradiol . 1994; 15: 201–212.
    OpenUrlAbstract/FREE Full Text
  48. ↵
    Dousset V, Brochet B, Vital A, et al. Lysolecithin-induced demyelination in primates: preliminary in vivo study with MR and magnetization transfer. AJNR Am J Neuroradiol . 1995; 16: 225–231.
    OpenUrlAbstract/FREE Full Text
  49. ↵
    Kimura H, Meaney DF, McGowan JC, et al. Magnetization transfer imaging of diffuse axonal injury following experimental brain injury in the pig: characterization by magnetization transfer ratio with histopathologic correlation. J Comput Assist Tomogr . 1996; 20: 540–546.
    OpenUrlCrossRefPubMed
  50. ↵
    van Buchem MA, McGowan JC, Kolson DL, Polansky M, Grossman RI. Quantitative volumetric magnetization transfer analysis in multiple sclerosis: estimation of macroscopic and microscopic disease burden. Magn Reson Med . 1996; 36: 632–636.
    OpenUrlPubMed
  51. ↵
    Filippi M, Iannucci G, Tortorella C, et al. Comparison of MS clinical phenotypes using conventional and magnetization transfer MRI. Neurology . 1999; 52: 588–594.
    OpenUrlAbstract/FREE Full Text
  52. ↵
    Rovaris M, Filippi M, Falautano M, et al. Relation between MR abnormalities and patterns of cognitive impairment in multiple sclerosis. Neurology . 1998; 50: 1601–1608.
    OpenUrlAbstract/FREE Full Text
  53. ↵
    van Buchem MA, Grossman RI, Armstrong C, et al. Correlation of volumetric magnetization transfer imaging with clinical data in MS. Neurology . 1998; 50: 1609–1617.
    OpenUrlAbstract/FREE Full Text
  54. ↵
    Iannucci G, Minicucci L, Rodegher M, Sormani MP, Comi G, Filippi M. Correlations between clinical and MRI involvement in multiple sclerosis: assessment using T1, T2 and MT histograms. J Neurol Sci . 1999; 171: 121–129.
    OpenUrlCrossRefPubMed
  55. ↵
    Gass A, Barker GJ, Kidd D, et al. Correlation of magnetization transfer ratio with disability in multiple sclerosis. Ann Neurol . 1994; 36: 62–67.
    OpenUrlCrossRefPubMed
  56. ↵
    Cercignani M, Bozzali M, Iannucci G, Comi G, Filippi M. Magnetisation transfer ratio and mean diffusivity of normal-appearing white and gray matter from patients with multiple sclerosis. J Neurol Neurosurg Psychiatry . 2001; 70: 311–317.
    OpenUrlAbstract/FREE Full Text
  57. ↵
    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: 470–475.
    OpenUrlAbstract/FREE Full Text
  58. ↵
    van Waesberghe JHTM, van Walderveen MA, Castelijns JA, et al. Patterns of lesion development in multiple sclerosis: longitudinal observations with T1-weighted spin-echo and magnetization MR. AJNR Am J Neuroradiol . 1998; 19: 675–683.
    OpenUrlAbstract
  59. ↵
    Goodkin DE, Rooney WD, Sloan R, et al. A serial study of new MS lesions and the white matter from which they arise. Neurology . 1998; 51: 1689–1697.
    OpenUrlAbstract/FREE Full Text
  60. ↵
    Dousset V, Gayou A, Brochet B, Caillé JM. Early structural changes in acute MS lesions assessed by serial magnetization transfer studies. Neurology . 1998; 51: 1150–1155.
    OpenUrlAbstract/FREE Full Text
  61. ↵
    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: 821–827.
    OpenUrlAbstract/FREE Full Text
  62. ↵
    Sormani MP, Iannucci G, Rocca MA, et al. Reproducibility of MTR histogram-derived measures of the brain in healthy volunteers. AJNR Am J Neuroradiol . 2000; 21: 133–136.
    OpenUrlAbstract/FREE Full Text
  63. ↵
    Filippi M, McGowan JC, Tortorella C. Magnetization transfer imaging in multiple sclerosis. In: Kappos L, Johnson K, Kesserling J, Radü E, eds. Multiple sclerosis: tissue destruction and repair. London: Martin Dunitz, 2001: 47–66.
  64. ↵
    Berry I, Barker GJ, Barkhof F, et al. A multicenter measurement of magnetization transfer ratio in normal white matter. J Magn Reson Imaging . 1999; 9: 441–446.
    OpenUrlCrossRefPubMed
  65. ↵
    Silver NC, Barker GJ, Miller DH. Standardization of magnetization transfer imaging for multicenter studies. Neurology . 1999; 53 (suppl 3): S33–S39.
    OpenUrl
  66. ↵
    Rose SE, Chen F, Chalk JB, et al. Loss of connectivity in Alzheimer’s disease: an evaluation of white matter tract integrity with colour coded MR diffusion tensor imaging. J Neurol Neurosurg Psychiatry . 2000; 69: 528–530.
    OpenUrlAbstract/FREE Full Text
  67. ↵
    Hanyu H, Sakurai H, Iwamoto T, et al. Diffusion-weighted imaging of the hippocampus and temporal white matter in Alzheimer’s disease. J Neurol Sci . 1998; 156: 195–200.
    OpenUrlCrossRefPubMed
  68. ↵
    Bozzali M, Franceschi M, Falini A, et al. Quantification of tissue damage in AD using diffusion tensor and magnetization transfer MRI. Neurology . 2001; 57: 1135–1137.
    OpenUrlAbstract/FREE Full Text
  69. ↵
    Nusbaum AO, Tang CY, Wei TC, Buchsbaum MS, Atlas SW. Whole-brain diffusion MR histograms differ between MS subtypes. Neurology . 2000; 54: 1421–1426.
    OpenUrlAbstract/FREE Full Text
  70. ↵
    Cercignani M, Iannucci G, Rocca MA, Comi G, Horsfield MA, Filippi M. Pathologic damage in MS assessed by diffusion-weighted and magnetization transfer MRI. Neurology . 2000; 54: 1139–1144.
    OpenUrlAbstract/FREE Full Text
  71. ↵
    Cercignani M, Inglese M, Pagani E, Comi G, Filippi M. Mean diffusivity and fractional anisotropy histograms in patients with multiple sclerosis. AJNR Am J Neuroradiol . 2001; 22: 952–958.
    OpenUrlAbstract/FREE Full Text
  72. ↵
    Castriota Scanderbeg A, Tomaiuolo F, Sabatini U, Nocentini U, Grasso MG, Caltagirone C. Demyelinating plaques in relapsing-remitting and secondary-progressive multiple sclerosis: assessment with diffusion MR imaging. AJNR Am J Neuroradiol . 2000; 21: 862–868.
    OpenUrlAbstract/FREE Full Text
  73. ↵
    Horsfield MA. Using diffusion-weighted MRI in multicenter clinical trials for multiple sclerosis. J Neurol Sci . 2001; 186 (suppl 1): S51–S54.
  74. ↵
    Grossman RI, Lenkinki RE, Ramer KN, Gonzalez-Scarano F, Cohen JA. MR proton spectroscopy in multiple sclerosis. AJNR Am J Neuroradiol . 1992; 13: 1535–1543.
    OpenUrlAbstract/FREE Full Text
  75. ↵
    Simmons ML, Frondoza CG, Coyle JT. Immunohistochemical localization of N-acetyl-aspartate with monoclonal antibodies. Neuroscience . 1991; 45: 37–45.
    OpenUrlCrossRefPubMed
  76. ↵
    Arnold DL, Reiss GT, Matthews PM, et al. Use of proton magnetic resonance spectroscopy for monitoring disease progression in multiple sclerosis. Ann Neurol . 1994; 36: 76–82.
    OpenUrlCrossRefPubMed
  77. ↵
    Matthews PM, Pioro E, Narayanan S, et al. Assessment of lesion pathology in multiple sclerosis using quantitative MRI morphometry and magnetic resonance spectroscopy. Brain . 1996; 119: 715–722.
    OpenUrlAbstract/FREE Full Text
  78. ↵
    De Stefano N, Matthews PM, Fu L, et al. Axonal damage correlates with disability in patients with relapsing-remitting multiple sclerosis: results of a longitudinal magnetic resonance spectroscopy study. Brain . 1998; 121: 1469–1477.
    OpenUrlAbstract/FREE Full Text
  79. ↵
    Gonen O, Catalaa I, Babb JS, et al. Total brain N-acetylaspartate: a new measure of disease load in MS. Neurology . 2000; 54: 15–19.
    OpenUrlAbstract/FREE Full Text
  80. ↵
    Davie CA, Hawkins CP, Barker GJ, et al. Serial proton magnetic resonance spectroscopy in acute multiple sclerosis lesions. Brain . 1994; 117: 49–58.
    OpenUrlAbstract/FREE Full Text
  81. ↵
    De Stefano N, Narayanan S, Francis GS, et al. Evidence of axonal damage in the early stages of multiple sclerosis and its relevance to disability. Arch Neurol . 2001; 58: 65–70.
    OpenUrlCrossRefPubMed
  82. ↵
    Husted CA, Goodin DS, Hugg JW, et al. Biochemical alterations in multiple sclerosis lesions and normal-appearing white matter detected by in vivo 31P and 1H spectroscopic imaging. Ann Neurol . 1994; 36: 157–165.
    OpenUrlCrossRefPubMed
  83. ↵
    Pan JW, Hetherington HP, Vaughan T, Mitchell G, Pohost GM, Whitaker JN. Evaluation of multiple sclerosis by 1H spectroscopic imaging at 4.1 T. Magn Reson Med . 1996; 36: 72–77.
    OpenUrlPubMed
  84. ↵
    Provencher SW. Estimation of metabolite concentrations from localized in vivo NMR spectra. Magn Reson Med . 1993; 30: 672–679.
    OpenUrlCrossRefPubMed
  85. ↵
    McGowan JC. Optimization and standardization of magnetic resonance spectroscopy techniques for multicenter longitudinal multiple sclerosis studies. In: Filippi M, Arnold DL, Comi G, eds. Magnetic resonance spectroscopy in multiple sclerosis. Berlin-Heidelberg-New York: Springer Verlag, 2000: 113–119.
  86. ↵
    Lee M, Reddy H, Johansen-Berg H, et al. The motor cortex shows adaptive functional changes to brain injury from multiple sclerosis. Ann Neurol . 2000; 47: 606–613.
    OpenUrlCrossRefPubMed
  87. ↵
    Reddy H, Narayanan S, Arnoutelis R, et al. Evidence for adaptive functional changes in the cerebral cortex with axonal injury from multiple sclerosis. Brain . 2000; 123: 2314–2320.
    OpenUrlAbstract/FREE Full Text
  88. ↵
    Rocca MA, Falini A, Colombo B, Scotti G, Comi G, Filippi M. Adaptive functional changes in the cerebral cortex of patients with nondisabling MS correlate with the extent of brain structural damage. Ann Neurol 2002;51 (in press).
  89. ↵
    Rocca MA, Matthews PM, Caputo D, et al. Evidence for widespread movement-associated functional MRI changes in patients with PPMS. Neurology . 2002; 58: 886–872.
    OpenUrl
  90. ↵
    Lublin FD, Reingold SC, National Multiple Sclerosis Society (USA) Task Force on Placebo-Controlled Clinical Trials in MS. Placebo-controlled clinical trials in multiple sclerosis: ethical considerations. Ann Neurol . 2001; 49: 677–681.
    OpenUrlCrossRefPubMed
  91. ↵
    Wolinsky JS, Narayana PA, Noseworthy JH, et al. Linomide in relapsing and secondary progressive MS: part II: MRI results. Neurology . 2000; 54: 1734–1741.
    OpenUrlAbstract/FREE Full Text
  92. ↵
    Mainero C, De Stefano N, Iannucci G, et al. Correlates of MS disability assessed in-vivo using aggregates of MR quantities. Neurology . 2001; 56: 1331–1334.
    OpenUrlAbstract/FREE Full Text

Letters: Rapid online correspondence

No comments have been published for this article.
Comment

REQUIREMENTS

If you are uploading a letter concerning an article:
You must have updated your disclosures within six months: http://submit.neurology.org

Your co-authors must send a completed Publishing Agreement Form to Neurology Staff (not necessary for the lead/corresponding author as the form below will suffice) before you upload your comment.

If you are responding to a comment that was written about an article you originally authored:
You (and co-authors) do not need to fill out forms or check disclosures as author forms are still valid
and apply to letter.

Submission specifications:

  • Submissions must be < 200 words with < 5 references. Reference 1 must be the article on which you are commenting.
  • Submissions should not have more than 5 authors. (Exception: original author replies can include all original authors of the article)
  • Submit only on articles published within 6 months of issue date.
  • Do not be redundant. Read any comments already posted on the article prior to submission.
  • Submitted comments are subject to editing and editor review prior to posting.

More guidelines and information on Disputes & Debates

Compose Comment

More information about text formats

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.
Author Information
NOTE: The first author must also be the corresponding author of the comment.
First or given name, e.g. 'Peter'.
Your last, or family, name, e.g. 'MacMoody'.
Your email address, e.g. higgs-boson@gmail.com
Your role and/or occupation, e.g. 'Orthopedic Surgeon'.
Your organization or institution (if applicable), e.g. 'Royal Free Hospital'.
Publishing Agreement
NOTE: All authors, besides the first/corresponding author, must complete a separate Publishing Agreement Form and provide via email to the editorial office before comments can be posted.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

Vertical Tabs

You May Also be Interested in

Back to top
Advertisement

Related Articles

  • No related articles found.

Topics Discussed

Alert Me