[Skip to Content]
Access to paid content on this site is currently suspended due to excessive activity being detected from your IP address 54.211.168.204. Please contact the publisher to request reinstatement.
Sign In
Individual Sign In
Create an Account
Institutional Sign In
OpenAthens Shibboleth
[Skip to Content Landing]
Download PDF
Figure.
Scatterplot of the correlation between the average gray matter (GM) magnetization transfer ratio (MTR) and changes in the Expanded Disability Status Scale (EDSS) score throughout 18 months (r = −0.44; P = .04).

Scatterplot of the correlation between the average gray matter (GM) magnetization transfer ratio (MTR) and changes in the Expanded Disability Status Scale (EDSS) score throughout 18 months (r = −0.44; P = .04).

Table. 
Conventional and Magnetization Transfer Magnetic Resonance Imaging Baseline Characteristics of 22 Patients With Relapsing-Remitting Multiple Sclerosis
Conventional and Magnetization Transfer Magnetic Resonance Imaging Baseline Characteristics of 22 Patients With Relapsing-Remitting Multiple Sclerosis
1.
Filippi  MTortorella  CRovaris  M Magnetic resonance imaging of multiple sclerosis. J Neuroimaging 2002;12289- 301
PubMedArticle
2.
Brex  PACiccarelli  OO'Riordan  JISailer  MThompson  AJMiller  DH A longitudinal study of abnormalities on MRI and disability from multiple sclerosis. N Engl J Med 2002;346158- 164
PubMedArticle
3.
Miller  DBarkhof  FMontalban  XThompson  AFilippi  M Clinically isolated syndromes suggestive of multiple sclerosis, part I: natural history, pathogenesis, diagnosis, and prognosis. Lancet Neurol 2005;4281- 288
PubMedArticle
4.
Miller  DBarkhof  FMontalban  XThompson  AFilippi  M Clinically isolated syndromes suggestive of multiple sclerosis, part 2: non-conventional MRI, recovery processes, and management. Lancet Neurol 2005;4341- 348
PubMedArticle
5.
Filippi  MPaty  DWKappos  L  et al.  Correlations between changes in disability and T2-weighted brain MRI activity in multiple sclerosis: a follow-up study. Neurology 1995;45255- 260
PubMedArticle
6.
Kappos  LMoeri  DRadue  EW  et al. Gadolinium MRI Meta-analysis Group, Predictive value of gadolinium-enhanced magnetic resonance imaging for relapse rate and changes in disability or impairment in multiple sclerosis: a meta-analysis. Lancet 1999;353964- 969
PubMedArticle
7.
Rovaris  MFilippi  MCalori  G  et al.  Intra-observer reproducibility in measuring new putative MR markers of demyelination and axonal loss in multiple sclerosis: a comparison with conventional T2-weighted images. J Neurol 1997;244266- 270
PubMedArticle
8.
Willoughby  EWPaty  DW Scales for rating impairment in multiple sclerosis: a critique. Neurology 1988;381793- 1798
PubMedArticle
9.
Filippi  MGrossman  RI MRI techniques to monitor MS evolution: the present and the future. Neurology 2002;581147- 1153
PubMedArticle
10.
Barkhof  F The clinico-radiological paradox in multiple sclerosis revisited. Curr Opin Neurol 2002;15239- 245
PubMedArticle
11.
Filippi  MRocca  MA Magnetization transfer magnetic resonance imaging in the assessment of neurological diseases. J Neuroimaging 2004;14303- 313
PubMedArticle
12.
Poser  CMPaty  DWScheinberg  L  et al.  New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983;13227- 231
PubMedArticle
13.
Kurtzke  JF Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 1983;331444- 1452
PubMedArticle
14.
Oreja-Guevara  CRovaris  MIannucci  G  et al.  Progressive gray matter damage in patients with relapsing-remitting multiple sclerosis: a longitudinal diffusion tensor magnetic resonance imaging study. Arch Neurol 2005;62578- 584
PubMedArticle
15.
Smith  SMZhang  YJenkinson  M  et al.  Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage 2002;17479- 489
PubMedArticle
16.
Rovaris  MGallo  AValsasina  P  et al.  Short-term accrual of gray matter pathology in patients with progressive multiple sclerosis: an in vivo study using diffusion tensor MRI. Neuroimage 2005;241139- 1146
PubMedArticle
17.
Cercignani  MIannucci  GRocca  MAComi  GHorsfield  MAFilippi  M Pathologic damage in MS assessed by diffusion-weighted and magnetization transfer MRI. Neurology 2000;541139- 1144
PubMedArticle
18.
Ashburner  JFriston  K Multimodal image coregistration and partitioning: a unified framework. Neuroimage 1997;6209- 217
PubMedArticle
19.
Cercignani  MBozzali  MIannucci  GComi  GFilippi  M Magnetisation transfer ratio and mean diffusivity of normal appearing white and grey matter from patients with multiple sclerosis. J Neurol Neurosurg Psychiatry 2001;70311- 317
PubMedArticle
20.
Iannucci  GMinicucci  LRodegher  MSormani  MPComi  GFilippi  M Correlations between clinical and MRI involvement in multiple sclerosis: assessment using T(1), T(2) and MT histograms. J Neurol Sci 1999;171121- 129
PubMedArticle
21.
Trapp  BDBo  LMork  SChang  A Pathogenesis of tissue injury in MS lesions. J Neuroimmunol 1999;9849- 56
PubMedArticle
22.
van Buchem  MAMcGowan  JCGrossman  RI Magnetization transfer histogram methodology: its clinical and neuropsychological correlates. Neurology 1999;53(suppl 3)S23- S28
PubMed
23.
van Waesberghe  JHKamphorst  WDe Groot  CJ  et al.  Axonal loss in multiple sclerosis lesions: magnetic resonance imaging insights into substrates of disability. Ann Neurol 1999;46747- 754
PubMedArticle
24.
Schmierer  KScaravilli  FAltmann  DRBarker  GJMiller  DH Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain. Ann Neurol 2004;56407- 415
PubMedArticle
25.
Rovaris  MAgosta  FSormani  MP  et al.  Conventional and magnetization transfer MRI predictors of clinical multiple sclerosis evolution: a medium-term follow-up study. Brain 2003;1262323- 2332
PubMedArticle
26.
Santos  ACNarayanan  Sde Stefano  N  et al.  Magnetization transfer can predict clinical evolution in patients with multiple sclerosis. J Neurol 2002;249662- 668
PubMedArticle
27.
Inglese  MBenedetti  BFilippi  M The relation between MRI measures of inflammation and neurodegeneration in multiple sclerosis. J Neurol Sci 2005;23315- 19
PubMedArticle
28.
Brownell  BHughes  JT The distribution of plaques in the cerebrum in multiple sclerosis. J Neurol Neurosurg Psychiatry 1962;25315- 320
PubMedArticle
29.
Lumsden  CE The neuropathology of multiple sclerosis.  In: Vinken  PJ, Bruyn  GW, eds. Handbook of Clinical Neurology. Vol9. Amsterdam, the Netherlands: North-Holland; 1970:217-309
30.
Kidd  DBarkhof  FMcConnell  RAlgra  PRAllen  IVRevesz  T Cortical lesions in multiple sclerosis. Brain 1999;12217- 26
PubMedArticle
31.
Geurts  JJBo  LPouwels  PJCastelijns  JAPolman  CHBarkhof  F Cortical lesions in multiple sclerosis: combined postmortem MR imaging and histopathology. AJNR Am J Neuroradiol 2005;26572- 577
PubMed
32.
Kapeller  PMcLean  MAGriffin  CM  et al.  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;248131- 138
PubMedArticle
33.
Chard  DTGriffin  CMMcLean  MA  et al.  Brain metabolite changes in cortical grey and normal-appearing white matter in clinically early relapsing-remitting multiple sclerosis. Brain 2002;1252342- 2352
PubMedArticle
34.
Ge  YGrossman  RIUdupa  JKBabb  JSKolson  DLMcGowan  JC Magnetization transfer ratio histogram analysis of gray matter in relapsing-remitting multiple sclerosis. AJNR Am J Neuroradiol 2001;22470- 475
PubMed
35.
Ge  YGrossman  RIUdupa  JKBabb  JSMannon  LJMcGowan  JC Magnetization transfer ratio histogram analysis of normal-appearing gray matter and normal-appearing white matter in multiple sclerosis. J Comput Assist Tomogr 2002;2662- 68
PubMedArticle
36.
Rovaris  MIannucci  GFalautano  M  et al.  Cognitive dysfunction in patients with mildly disabling relapsing-remitting multiple sclerosis: an exploratory study with diffusion tensor MR imaging. J Neurol Sci 2002;195103- 109
PubMedArticle
37.
Chard  DTGriffin  CMRashid  W  et al.  Progressive grey matter atrophy in clinically early relapsing-remitting multiple sclerosis. Mult Scler 2004;10387- 391
PubMedArticle
38.
Cifelli  AArridge  MJezzard  PEsiri  MMPalace  JMatthews  PM Thalamic neurodegeneration in multiple sclerosis. Ann Neurol 2002;52650- 653
PubMedArticle
39.
Wylezinska  MCifelli  AJezzard  PPalace  JAlecci  MMatthews  PM Thalamic neurodegeneration in relapsing-remitting multiple sclerosis. Neurology 2003;601949- 1954
PubMedArticle
40.
Fabiano  AJSharma  JWeinstock-Guttman  B  et al.  Thalamic involvement in multiple sclerosis: a diffusion-weighted magnetic resonance imaging study. J Neuroimaging 2003;13307- 314
PubMedArticle
41.
Davies  GRAltmann  DRRashid  W  et al.  Emergence of thalamic magnetization transfer ratio abnormality in early relapsing-remitting multiple sclerosis. Mult Scler 2005;11276- 281
PubMedArticle
42.
Audoin  BRanjeva  JPvan Au Dong  M  et al.  Voxel-based analysis of MTR images: a method to locate gray matter abnormalities in patients at the earliest stage of multiple sclerosis. J Magn Reson Imaging 2004;20765- 771
PubMedArticle
43.
Valsasina  PBenedetti  BRovaris  MSormani  MPComi  GFilippi  M Evidence for progressive gray matter loss in patients with relapsing-remitting MS. Neurology 2005;651126- 1128
PubMedArticle
44.
Peterson  JWBo  LMork  SChang  ATrapp  BD Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Ann Neurol 2001;50389- 400
PubMedArticle
45.
Evangelou  NKonz  DEsiri  MMSmith  SPalace  JMatthews  PM Regional axonal loss in the corpus callosum correlates with cerebral white matter lesion volume and distribution in multiple sclerosis. Brain 2000;1231845- 1849
PubMedArticle
46.
Rizvi  SAAgius  MA Current approved options for treating patients with multiple sclerosis. Neurology 2004;63(suppl 6)S8- S14
PubMedArticle
47.
Paolillo  APozzilli  CGiugni  E  et al.  A 6-year clinical and MRI follow-up study of patients with relapsing-remitting multiple sclerosis treated with interferon-beta. Eur J Neurol 2002;9645- 655
PubMedArticle
48.
Cutter  GRBaier  MLRudick  RA  et al.  Development of a multiple sclerosis functional composite as a clinical trial outcome measure. Brain 1999;122871- 882
PubMedArticle
Original Contribution
May 2006

Magnetization Transfer Magnetic Resonance Imaging and Clinical Changes in Patients With Relapsing-Remitting Multiple Sclerosis

Author Affiliations

Author Affiliations: Neuroimaging Research Unit, Department of Neurology, Scientific Institute and University Ospedale San Raffaele (Drs Oreja-Guevara, Sormani, and Filippi and Mr Charil), and Department of Neurology (Drs Caputo and Cavarretta) and MRI Research Group (Dr Filippi), Fondazione Don Gnocchi, Milan, Italy; and Dipartimento di Scienze della Salute, Biostatistics Unit, University of Genoa, Genoa, Italy (Dr Sormani).

Arch Neurol. 2006;63(5):736-740. doi:10.1001/archneur.63.5.736
Abstract

Background  Magnetization transfer (MT) magnetic resonance imaging (MRI) can provide in vivo quantitative estimates of microscopic tissue damage in normal-appearing white matter (NAWM) and gray matter (GM) from patients with multiple sclerosis (MS).

Objective  To determine whether a onetime MT MRI can provide markers of short-term disease evolution in patients with relapsing-remitting MS.

Design  Eighteen-month observational study.

Setting  Neuroimaging Research Unit, Scientific Institute and University Ospedale San Raffaele.

Patients  Twenty-two patients with untreated relapsing-remitting MS.

Main Outcome Measures  Relapse rate; disability according to the Expanded Disability Status Scale (EDSS); dual-echo, 2-dimensional gradient echo with and without a saturation MT pulse and T1-weighted MRIs of the brain; and MT ratio (MTR) histograms for NAWM and GM.

Results  During the study period, 13 patients (59%) experienced 25 relapses. The median EDSS score was 1.25 (range, 0-3.5) at study entry and 1.75 (range, 0-3) at study exit. Significant, although moderate, correlations were found between average GM MTR values at baseline and EDSS changes during the study period (r = −0.44; P = .04). A trend was observed for the correlation between NAWM MTR values at baseline and the EDSS changes throughout 18 months (r = −0.42; P = .05). For the relation between EDSS changes and baseline GM MTR, the slope of the regression line was −0.5 (95% confidence interval, −1.0 to 0.0), indicating that a decrease in the baseline GM MTR of 1% predicted an increase in the EDSS score of 0.5 point throughout the 18 months.

Conclusion  This study indicates that a “snapshot” MT MRI assessment detects subtle brain tissue changes that are associated with short-term disability accumulation in patients with relapsing-remitting MS.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system that has a highly unpredictable clinical course. Although conventional magnetic resonance imaging (cMRI) is sensitive in detecting MS lesions,1 it makes reliable predictions about subsequent evolution of the disease only in patients with the clinically isolated syndrome suggestive of MS.24 On the contrary, the correlation between MRI findings and development of disability remains modest, if any, in patients with definite MS.57 This is likely the result, on the one hand, of the inherent weaknesses of the clinical scales used to rate disability8 and, on the other hand, of the limitations of cMRI. These limitations include the lack of histopathologic specificity to the various substrates of MS, the failure to reflect functional compensatory mechanisms of the cortex, and perhaps most important, its inability to detect microscopic pathologic changes that occur in the normal-appearing brain tissue. 911

The possibility of overcoming some of these limitations has come with the advent and clinical application of nonconventional MRI techniques that have the potential to provide a more complete picture of the complex pathologic changes of MS.9 Among these techniques, magnetization transfer (MT) MRI is one of the most promising.11 The present MT ratio (MTR) histogram–based study was designed to determine whether a onetime MT MRI evaluation can provide prognostic markers of the short-term disease evolution in patients with relapsing-remitting (RR) MS.

METHODS
PATIENTS

To be included in the study, patients had to have clinically definite MS12 for at least 1 year and an RR course. To avoid the potential confounding effect of disease-modifying treatments, additional inclusion criteria were the absence of previous immunosuppressive or immunomodulating treatments and the absence of disease-modifying treatments during the study period. Patients were fully informed about available disease-modifying treatments but did not receive any of them for either medical or personal reasons. Relapse rate and Expanded Disability Status Scale (EDSS)13 scores were assessed at regular visits at baseline and then every 3 months for 18 months. All patients were evaluated by a single neurologist (R.C.) who was blinded to the MRI findings. In case of symptoms suggestive of a clinical relapse, patients were instructed to contact the same neurologist for additional visits and treatment decisions. Clinical relapses were always treated with intravenous methylprednisolone, 1 g/d, for 3 to 5 consecutive days (with no subsequent tapering). In cases of recent relapses, EDSS score deterioration had to be confirmed by an additional visit after 1 month. The experimental procedures were approved by the local ethics committee, and written informed consent was obtained from each patient before study inclusion.

IMAGE ACQUISITION

This study was part of a larger research protocol that assessed longitudinal brain diffusion tensor MRI changes in patients with RRMS.14 Because of the duration of the overall MRI acquisition protocol, only 22 of the 26 patients enrolled in the diffusion tensor MRI study consented to undergo the additional studies needed to acquire MTR images. Using a 1.5-T scanner on a regular course of maintenance, the following sequences were obtained at baseline from all patients: (1) dual-echo turbo spin-echo (repetition time [TR]/echo time 1 [TE1]/echo time 2 [TE2] = 3300/16/98 milliseconds; echo train length = 5); (2) T1-weighted conventional spin-echo (TR/TE = 768/15 milliseconds); and (3) 2-dimensional gradient echo (TR/TE = 600/12 milliseconds, flip angle = 20°) with and without an off-resonance radiofrequency saturation pulse. The radiofrequency saturation pulse was 1.5 kHz below the water frequency, with a gaussian envelope of duration of 16.4 milliseconds, a bandwidth of 250 Hz, and an amplitude of 3.4 × 10−6 T. For dual-echo and T1-weighted images, 24 contiguous axial sections were obtained with 5-mm thickness, 256 × 256-mm matrix size, and 250 × 250-mm field of view. The sections were positioned to run parallel to a line that joins the most inferoanterior and inferoposterior parts of the corpus callosum. The MT MRIs were obtained with the same acquisition parameters except for the number of sections, which was 20. The set of sections for the MT images was positioned to obtain the same central 20 sections as for the dual-echo and T1-weighted images.

IMAGE ANALYSIS

Two experienced observers (C.O.-G. and A.C.), without knowing to whom the images belonged, identified by consensus the hyperintense lesions on the proton density–weighted studies and the hypointense lesions on the T1-weighted images. The T2-weighted images were always used to increase confidence in lesion identification. Total T2-hyperintense and T1-hypointense lesion volumes were measured by a single observer (C.O.-G.), using a local thresholding technique for lesion segmentation.7 Using T1-weighted images and SIENAx (the cross-sectional version of the software Structural Imaging Evaluation of Normalized Atrophy),15 normalized volumes of white matter (WM) and gray matter (GM) were estimated at baseline.

After coregistration of the 2 gradient echo images using a surface-matching technique based on mutual information, MTR maps were derived pixel by pixel.16 Extracerebral tissue was removed from MTR maps using a local thresholding segmentation technique, and the resulting images were coregistered with the T2-weighted images.16 Average lesion MTR was measured as previously reported.17 The GM, WM, and cerebrospinal fluid were automatically segmented from dual-echo images using SPM99 and maximum image inhomogeneity correction,18 and whenever present, T2-hyperintense lesions were masked out from the segmented tissues. The resulting masks were superimposed onto the coregistered MTR maps, and the corresponding MTR histograms of the normal-appearing WM (NAWM) and GM were produced.19 For each histogram, the average MTR was calculated. Given the strong correlation between average MTR and the other histogram metrics,20 only this quantity was a priori included in the analysis to minimize the number of comparisons and therefore reduce the risk of type I errors.

STATISTICAL ANALYSIS

Correlations were performed with the Spearman rank correlation coefficient. Two regression lines relating changes in the EDSS (dependent variable) to the values of baseline GM MTR and NAWM MTR (independent variables) were fitted to estimate the extent of the EDSS score deterioration predicted by the reduction in each percentage change of baseline MTR. Because of the exploratory nature of this study, no correction for multiple testing was performed; as a consequence, the reported P values should be viewed with caution.

RESULTS

We studied 22 patients with RRMS (15 women and 7 men; mean age, 36.6 years; age range, 25-50 years; mean disease duration, 10.4 years; disease duration range, 1-23 years). The median EDSS score was 1.25 (range, 0-3.5) at study entry and 1.75 (range, 0-3) at study exit. During the follow-up, 13 patients (59%) experienced 25 relapses. The Table reports baseline cMRI and MT MRI findings from the 22 patients with RRMS.

A significant, albeit moderate, correlation was found between average GM (r = −0.44; P = .04) MTR values at baseline and EDSS changes throughout the study period (Figure 1). A trend was observed (r = −0.42; P = .05) for the correlation between NAWM MTR values at baseline and the EDSS changes throughout 18 months. The correlations between on-study relapses and either baseline GM MTR (r = −0.16; P = .49) or baseline NAWM MTR (r = −0.25; P = .26) were both weak and not significant. A trend was observed between EDSS changes and on-study relapses (r = 0.40; P = .07). After adjusting for the number of on-study relapses, the partial correlation coefficients of the correlation between EDSS changes and baseline GM MTR (r = −0.41; P = .06) remained virtually unchanged.

The correlations of baseline EDSS with baseline average GM MTR (r = 0.26; P = .24) and baseline average WM MTR (r = 0.29; P = .20) were both weak and not statistically significant. No significant correlations were found between baseline GM and WM volumes or between T2 and T1 lesion volume and EDSS score changes at study end. No significant correlation was found between average lesion MTR and EDSS changes at study end. For the relation between EDSS changes and baseline GM MTR, the slope of the regression line was −0.5 (95% confidence interval, −1.0 to 0.0), indicating that a decrease in the baseline GM MTR of 1% predicted an increase in the EDSS score of 0.5 point throughout the 18 months.

COMMENT

Despite its high sensitivity to detect the presence of MS lesions, cMRI fails to provide specific information about the nature of the pathologic substrates of MS lesions, which include edema, demyelination, remyelination, gliosis, and axonal loss.21 In addition, the occult damage to the normal-appearing brain tissue remains unaccounted for by cMRI, which, together with the limitations of the EDSS, is likely to contribute to the poor correlations that have been reported to date between clinical and MRI findings in patients with definite MS.10

Histogram-based analysis of MT MRI has the potential to provide information about the microstructural damage that is invisible on cMRI and that reflects the global or tissue-specific degree of damage.22 The MTR reduction was found to be strongly correlated with the percentage of residual axons and the degree of demyelination.23,24 Preliminary studies have reported promising findings on the predictive value of MT MRI on the medium-term clinical evolution of the disease.25,26 However, the predictive value of a single MT MRI on the short-term clinical deterioration in MS is still unclear, despite the fact that the possibility of deriving prognostic information from a single baseline study is extremely appealing in terms of cost and labor saving, especially in the context of clinical trials for patient selection and stratification.

The present study shows a moderate correlation between average GM MTR at baseline and EDSS score changes during a follow-up of 18 months and a trend for the correlation between average WM MTR at baseline and EDSS score changes at study end. Interestingly, no correlation was observed between average GM MTR and on-study relapse rate, and the strength of the correlation between baseline GM MTR and EDSS score change during the study period remained unchanged when adjusting for on-study relapse. This finding confirms the notion that the inflammatory component of MS is not the only factor associated with accumulation of disability since the RR phase of the disease.4,27 No correlations were found between EDSS score changes and baseline T2 and T1 lesion volumes, as well as with GM and WM volumes. Additionally, no significant correlation was found between baseline average lesion MTR and EDSS score changes at study end. This finding suggests that in established MS, the extent of diffuse microstructural damage in the GM at baseline, rather than the morphologic characteristics of brain tissues, the lesion load as seen on cMRI, or even the microscopic damage occurring within lesions, is a reliable indicator of subsequent clinical deterioration in a time frame close to that typically used in the context of MS trials.

Postmortem studies have shown that MS does not spare cerebral GM.2831 In agreement with this, an increasing body of MRI evidence shows that GM damage is a consistent feature of MS in its RR phase.14,19,3242 Proton magnetic resonance spectroscopy showed significantly reduced concentrations of the neuronal marker N-acetylaspartate in the cortical GM of mildly impaired patients with RRMS with short disease durations.32,33 Other investigators have revealed reduced MTR and abnormal diffusivity in the GM of patients with RRMS,19,34,35 which are correlated with the degree of cognitive impairment.36 Recent work has also shown that GM damage in RRMS accumulates over time.14,37,43 The development and accumulation of lesions in the GM are among the possible explanations for the observed changes in the GM of patients with RRMS. Frequently, GM lesions are present, and although they are usually undetected by cMRI, they represent a significant portion of the overall brain lesion burden in MS.2831 Transected neuritis, transected axons, and apoptotic neurons have all been observed within cortical demyelinated lesions.44 Deep GM structures such as the thalamus are also affected by MS, as shown by a reduction in N-acetylaspartate concentrations, thalamic volume,38,39 and thalamic MTR41 and an increase in water diffusion.40 Therefore, the presence of lesions in the cortex and deep GM and the progressive retrograde degeneration of neurons after fiber transection within WM lesions45 could likely explain the reduction of MTR values in the GM.

Although a significant correlation between baseline NAWM MTR values and changes in EDSS score over time has been reported previously,26 we found a trend that most likely would have reached statistical significance with increased degrees of freedom. This partial discrepancy with previous studies could be explained by differences in durations over which disability was evaluated, because our clinical evolution was measured during a relatively short period. Another reason might be that in addition to patients with RRMS, the previous study included patients with a secondary progressive disease course.26 The inclusion of a homogeneous group of mildly impaired patients with RRMS might be viewed as a strength of the present study; these are the patients who currently are considered to benefit most from treatment.46 In addition, the clinical, demographic, and cMRI characteristics of this patient sample were similar to those of the cohort enrolled in the diffusion tensor MRI study of the brain,14 which were in the range expected from previous natural history studies.6,47

An explanation for the slightly better prognostic value of GM MTR over that of WM MTR might lie in the fact that GM abnormalities reflect direct and indirect (through axonal damage) neuronal abnormalities, which in turn are more likely to cause irreversible disability than less destructive changes that occur in the NAWM (such as inflammatory edema and demyelination), which can also cause MTR reductions.

One limitation of the present study may come from the use of the EDSS to rate clinical disability. The National Multiple Sclerosis Society's Advisory Committee on Clinical Trials of New Agents in Multiple Sclerosis appointed a task force that developed the Multiple Sclerosis Functional Composite as an improved clinical outcome measure48 to overcome the limitations of the EDSS.8 The advantages of this measure are that it encompasses the major clinical dimensions of arm, leg, and cognitive function and that it is more sensitive to changes during short periods than the EDSS.48 Although this would suggest that the use of the Multiple Sclerosis Functional Composite as a clinical scale to rate the patients' disability could yield better correlations between baseline MTR-derived measures and clinical disability changes throughout relatively short periods, the present study was designed at a time when the Multiple Sclerosis Functional Composite had not yet been fully validated and its use was still limited to a few centers. Nevertheless, most MS studies (including trials) are still conducted by rating disability with the EDSS (alone or in combination with other measures), which should make our results more easily interpreted against the background of existing literature on the topic. Additional studies with larger populations and better clinical outcome measures are now warranted.

Back to top
Article Information

Correspondence: Massimo Filippi, MD, Neuroimaging Research Unit, Department of Neurology, Scientific Institute and University Ospedale San Raffaele, Via Olgettina 60, 20132 Milan, Italy (filippi.massimo@hsr.it).

Accepted for Publication: January 13, 2006.

Funding/Support: Dr Oreja-Guevara was supported by an educational grant from the European Neurological Society.

References
1.
Filippi  MTortorella  CRovaris  M Magnetic resonance imaging of multiple sclerosis. J Neuroimaging 2002;12289- 301
PubMedArticle
2.
Brex  PACiccarelli  OO'Riordan  JISailer  MThompson  AJMiller  DH A longitudinal study of abnormalities on MRI and disability from multiple sclerosis. N Engl J Med 2002;346158- 164
PubMedArticle
3.
Miller  DBarkhof  FMontalban  XThompson  AFilippi  M Clinically isolated syndromes suggestive of multiple sclerosis, part I: natural history, pathogenesis, diagnosis, and prognosis. Lancet Neurol 2005;4281- 288
PubMedArticle
4.
Miller  DBarkhof  FMontalban  XThompson  AFilippi  M Clinically isolated syndromes suggestive of multiple sclerosis, part 2: non-conventional MRI, recovery processes, and management. Lancet Neurol 2005;4341- 348
PubMedArticle
5.
Filippi  MPaty  DWKappos  L  et al.  Correlations between changes in disability and T2-weighted brain MRI activity in multiple sclerosis: a follow-up study. Neurology 1995;45255- 260
PubMedArticle
6.
Kappos  LMoeri  DRadue  EW  et al. Gadolinium MRI Meta-analysis Group, Predictive value of gadolinium-enhanced magnetic resonance imaging for relapse rate and changes in disability or impairment in multiple sclerosis: a meta-analysis. Lancet 1999;353964- 969
PubMedArticle
7.
Rovaris  MFilippi  MCalori  G  et al.  Intra-observer reproducibility in measuring new putative MR markers of demyelination and axonal loss in multiple sclerosis: a comparison with conventional T2-weighted images. J Neurol 1997;244266- 270
PubMedArticle
8.
Willoughby  EWPaty  DW Scales for rating impairment in multiple sclerosis: a critique. Neurology 1988;381793- 1798
PubMedArticle
9.
Filippi  MGrossman  RI MRI techniques to monitor MS evolution: the present and the future. Neurology 2002;581147- 1153
PubMedArticle
10.
Barkhof  F The clinico-radiological paradox in multiple sclerosis revisited. Curr Opin Neurol 2002;15239- 245
PubMedArticle
11.
Filippi  MRocca  MA Magnetization transfer magnetic resonance imaging in the assessment of neurological diseases. J Neuroimaging 2004;14303- 313
PubMedArticle
12.
Poser  CMPaty  DWScheinberg  L  et al.  New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983;13227- 231
PubMedArticle
13.
Kurtzke  JF Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 1983;331444- 1452
PubMedArticle
14.
Oreja-Guevara  CRovaris  MIannucci  G  et al.  Progressive gray matter damage in patients with relapsing-remitting multiple sclerosis: a longitudinal diffusion tensor magnetic resonance imaging study. Arch Neurol 2005;62578- 584
PubMedArticle
15.
Smith  SMZhang  YJenkinson  M  et al.  Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage 2002;17479- 489
PubMedArticle
16.
Rovaris  MGallo  AValsasina  P  et al.  Short-term accrual of gray matter pathology in patients with progressive multiple sclerosis: an in vivo study using diffusion tensor MRI. Neuroimage 2005;241139- 1146
PubMedArticle
17.
Cercignani  MIannucci  GRocca  MAComi  GHorsfield  MAFilippi  M Pathologic damage in MS assessed by diffusion-weighted and magnetization transfer MRI. Neurology 2000;541139- 1144
PubMedArticle
18.
Ashburner  JFriston  K Multimodal image coregistration and partitioning: a unified framework. Neuroimage 1997;6209- 217
PubMedArticle
19.
Cercignani  MBozzali  MIannucci  GComi  GFilippi  M Magnetisation transfer ratio and mean diffusivity of normal appearing white and grey matter from patients with multiple sclerosis. J Neurol Neurosurg Psychiatry 2001;70311- 317
PubMedArticle
20.
Iannucci  GMinicucci  LRodegher  MSormani  MPComi  GFilippi  M Correlations between clinical and MRI involvement in multiple sclerosis: assessment using T(1), T(2) and MT histograms. J Neurol Sci 1999;171121- 129
PubMedArticle
21.
Trapp  BDBo  LMork  SChang  A Pathogenesis of tissue injury in MS lesions. J Neuroimmunol 1999;9849- 56
PubMedArticle
22.
van Buchem  MAMcGowan  JCGrossman  RI Magnetization transfer histogram methodology: its clinical and neuropsychological correlates. Neurology 1999;53(suppl 3)S23- S28
PubMed
23.
van Waesberghe  JHKamphorst  WDe Groot  CJ  et al.  Axonal loss in multiple sclerosis lesions: magnetic resonance imaging insights into substrates of disability. Ann Neurol 1999;46747- 754
PubMedArticle
24.
Schmierer  KScaravilli  FAltmann  DRBarker  GJMiller  DH Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain. Ann Neurol 2004;56407- 415
PubMedArticle
25.
Rovaris  MAgosta  FSormani  MP  et al.  Conventional and magnetization transfer MRI predictors of clinical multiple sclerosis evolution: a medium-term follow-up study. Brain 2003;1262323- 2332
PubMedArticle
26.
Santos  ACNarayanan  Sde Stefano  N  et al.  Magnetization transfer can predict clinical evolution in patients with multiple sclerosis. J Neurol 2002;249662- 668
PubMedArticle
27.
Inglese  MBenedetti  BFilippi  M The relation between MRI measures of inflammation and neurodegeneration in multiple sclerosis. J Neurol Sci 2005;23315- 19
PubMedArticle
28.
Brownell  BHughes  JT The distribution of plaques in the cerebrum in multiple sclerosis. J Neurol Neurosurg Psychiatry 1962;25315- 320
PubMedArticle
29.
Lumsden  CE The neuropathology of multiple sclerosis.  In: Vinken  PJ, Bruyn  GW, eds. Handbook of Clinical Neurology. Vol9. Amsterdam, the Netherlands: North-Holland; 1970:217-309
30.
Kidd  DBarkhof  FMcConnell  RAlgra  PRAllen  IVRevesz  T Cortical lesions in multiple sclerosis. Brain 1999;12217- 26
PubMedArticle
31.
Geurts  JJBo  LPouwels  PJCastelijns  JAPolman  CHBarkhof  F Cortical lesions in multiple sclerosis: combined postmortem MR imaging and histopathology. AJNR Am J Neuroradiol 2005;26572- 577
PubMed
32.
Kapeller  PMcLean  MAGriffin  CM  et al.  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;248131- 138
PubMedArticle
33.
Chard  DTGriffin  CMMcLean  MA  et al.  Brain metabolite changes in cortical grey and normal-appearing white matter in clinically early relapsing-remitting multiple sclerosis. Brain 2002;1252342- 2352
PubMedArticle
34.
Ge  YGrossman  RIUdupa  JKBabb  JSKolson  DLMcGowan  JC Magnetization transfer ratio histogram analysis of gray matter in relapsing-remitting multiple sclerosis. AJNR Am J Neuroradiol 2001;22470- 475
PubMed
35.
Ge  YGrossman  RIUdupa  JKBabb  JSMannon  LJMcGowan  JC Magnetization transfer ratio histogram analysis of normal-appearing gray matter and normal-appearing white matter in multiple sclerosis. J Comput Assist Tomogr 2002;2662- 68
PubMedArticle
36.
Rovaris  MIannucci  GFalautano  M  et al.  Cognitive dysfunction in patients with mildly disabling relapsing-remitting multiple sclerosis: an exploratory study with diffusion tensor MR imaging. J Neurol Sci 2002;195103- 109
PubMedArticle
37.
Chard  DTGriffin  CMRashid  W  et al.  Progressive grey matter atrophy in clinically early relapsing-remitting multiple sclerosis. Mult Scler 2004;10387- 391
PubMedArticle
38.
Cifelli  AArridge  MJezzard  PEsiri  MMPalace  JMatthews  PM Thalamic neurodegeneration in multiple sclerosis. Ann Neurol 2002;52650- 653
PubMedArticle
39.
Wylezinska  MCifelli  AJezzard  PPalace  JAlecci  MMatthews  PM Thalamic neurodegeneration in relapsing-remitting multiple sclerosis. Neurology 2003;601949- 1954
PubMedArticle
40.
Fabiano  AJSharma  JWeinstock-Guttman  B  et al.  Thalamic involvement in multiple sclerosis: a diffusion-weighted magnetic resonance imaging study. J Neuroimaging 2003;13307- 314
PubMedArticle
41.
Davies  GRAltmann  DRRashid  W  et al.  Emergence of thalamic magnetization transfer ratio abnormality in early relapsing-remitting multiple sclerosis. Mult Scler 2005;11276- 281
PubMedArticle
42.
Audoin  BRanjeva  JPvan Au Dong  M  et al.  Voxel-based analysis of MTR images: a method to locate gray matter abnormalities in patients at the earliest stage of multiple sclerosis. J Magn Reson Imaging 2004;20765- 771
PubMedArticle
43.
Valsasina  PBenedetti  BRovaris  MSormani  MPComi  GFilippi  M Evidence for progressive gray matter loss in patients with relapsing-remitting MS. Neurology 2005;651126- 1128
PubMedArticle
44.
Peterson  JWBo  LMork  SChang  ATrapp  BD Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Ann Neurol 2001;50389- 400
PubMedArticle
45.
Evangelou  NKonz  DEsiri  MMSmith  SPalace  JMatthews  PM Regional axonal loss in the corpus callosum correlates with cerebral white matter lesion volume and distribution in multiple sclerosis. Brain 2000;1231845- 1849
PubMedArticle
46.
Rizvi  SAAgius  MA Current approved options for treating patients with multiple sclerosis. Neurology 2004;63(suppl 6)S8- S14
PubMedArticle
47.
Paolillo  APozzilli  CGiugni  E  et al.  A 6-year clinical and MRI follow-up study of patients with relapsing-remitting multiple sclerosis treated with interferon-beta. Eur J Neurol 2002;9645- 655
PubMedArticle
48.
Cutter  GRBaier  MLRudick  RA  et al.  Development of a multiple sclerosis functional composite as a clinical trial outcome measure. Brain 1999;122871- 882
PubMedArticle
×