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Published online before print November 4, 2004, 10.1148/radiol.2341031895
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(Radiology 2005;234:211-217.)
© RSNA, 2004

Neuroradiology

Relapsing-Remitting Multiple Sclerosis: Metabolic Abnormality in Nonenhancing Lesions and Normal-appearing White Matter at MR Imaging: Initial Experience1

Juan He, MD, Matilde Inglese, MD, Belinda S. Y. Li, PhD, James S. Babb, PhD, Robert I. Grossman, MD and Oded Gonen, PhD

1 From the Department of Radiology, New York University School of Medicine, 650 First Ave, New York, NY 10016. Received November 25, 2003; revision requested February 6, 2004; revision received February 19; accepted May 11. Supported by National Institutes of Health grants NS37739, NS29029, and EB01015. Address correspondence to O.G. (e-mail: oded.gonen@med.nyu.edu).


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
PURPOSE: To quantify, with three-dimensional proton magnetic resonance (MR) spectroscopy, metabolic characteristics of normal-appearing white matter and nonenhancing lesions in patients with relapsing-remitting multiple sclerosis (MS).

MATERIALS AND METHODS: Institutional review board approval and informed patient consent were obtained. Nine patients with relapsing-remitting MS (six women, three men) and nine age-matched control subjects (seven women, two men) were studied with T1- and T2-weighted MR imaging and three-dimensional proton MR spectroscopy at spatial resolution less than a cubic centimeter. Absolute N-acetylaspartate (NAA), creatine (Cr), and choline (Cho) levels were obtained from 171 voxels: 66 from lesions on T2-weighted MR images (43 hypointense and 23 isointense on T1-weighted MR images), 31 from normal-appearing white matter, and 74 from analogous normal white matter regions on images in control subjects.

RESULTS: Mean NAA level in hypointense lesions (5.30 mmol/L ± 2.27 [standard deviation]) was significantly lower (P ≤ .05) than that in isointense lesions (7.82 mmol/L ± 2.28), normal-appearing white matter (7.37 mmol/L ± 1.71), and normal white matter in control subjects (8.89 mmol/L ± 1.54). Cho (1.79 mmol/L ± 0.65) and Cr (5.64 mmol/L ± 1.50) levels in isointense lesions were indistinguishable from those in normal-appearing white matter (1.74 mmol/L ± 0.46 and 4.99 mmol/L ± 0.97, respectively) but were significantly higher (Cho, 20%; Cr, 24%) than those in normal white matter in control subjects (1.44 mmol/L ± 0.40 and 4.30 mmol/L ± 1.32, respectively). NAA, Cho, and Cr levels in normal-appearing white matter were significantly different than those in normal white matter in control subjects (NAA, 20% lower; Cho, 14% higher; and Cr, 17% higher).

CONCLUSION: Abnormal metabolic activity persists in all MS tissue types. Increased Cr and Cho levels suggest (a) ongoing gliosis and attempted remyelination in isointense lesions on T1-weighted MR images and (b) membrane turnover (de- and remyelination), in addition to increased cellularity (gliosis, inflammation) in normal-appearing white matter.

© RSNA, 2004


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
In the relapsing-remitting phase of multiple sclerosis (MS), new white matter lesions occur two to 15 times more frequently than clinical relapses (1). The conspicuity of these lesions on T2-weighted magnetic resonance (MR) images has made it both the imaging modality of choice in MS and a secondary outcome measure in phase III clinical trials (1,2). Yet, despite its usefulness, T2-weighted MR imaging is insensitive to microscopic pathologic changes in normal-appearing white matter. Other MR measurements, such as magnetization transfer, diffusion-weighted MR imaging, or proton MR spectroscopy, have consistently suggested structural and metabolic differences among lesions, reflecting various underlying processes ranging from complete recovery to permanent tissue loss (3,4). Even on T1-weighted MR images, hypointensities (or "black holes") thought to represent tissue destruction can exhibit variable tissue loss, ongoing disease activity, and tissue repair (5–11).

While acute lesions on T1-weighted MR images may be either iso- (20%) or hypointense (80%) relative to the surrounding normal-appearing white matter (7), 40% of the former will have turned into the latter at follow-up (7,12). A previous serial study (10) involved the comparison of signal intensity and histopathologic findings in lesions sampled for biopsy at initial examination and at follow-up. Axonal loss and demyelination were associated with decreases in signal intensity, while remyelination was associated with increases in signal intensity. In acute lesions, however, hypointensity was not associated with either axonal loss or demyelinating activity (10). This may be due to the dependence of signal intensity on the MR sequence parameters, such as echo time, inversion time, repetition time, and gain.

Unlike MR imaging, proton MR spectroscopy provides direct metabolic information on the integrity of axons and membranes in lesions and normal-appearing white matter (13) through measurements of N-acetylaspartate (NAA), total choline (Cho), and creatine (Cr). Three-dimensional proton MR spectroscopy is particularly appropriate for study of multiple tissue types, since (a) large volumes of interest can be covered at spatial resolution less than a cubic centimeter, (b) signal-to-noise-ratio for a given examination time is optimal (14), and (c) voxel shifts allow localization grid positioning over lesions in postprocessing to minimize partial volume contamination (11,14). Our goal, therefore, was to quantify, with three-dimensional proton MR spectroscopy, the metabolic characteristics of normal-appearing white matter and nonenhancing lesions in patients with relapsing-remitting MS.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Patients and Control Subjects
Nine patients with relapsing-remitting MS (six women, three men; mean age, 38.9 years; age range, 26–47 years) were recruited from an ongoing serial study (institutional review board approved) of relapsing-remitting MS. Informed consent was obtained from each patient for that ongoing study. Patients who had experienced relapses in the preceding 3 months or who had enhancing lesions on contrast material–enhanced T1-weighted MR images at the time of enrollment were excluded. Mean disease duration from the time of confirmed diagnosis was 6.4 years (3–8), and median score according to the expanded disability status scale was 2.5 (range, 0–6).

Nine age-matched healthy volunteers (seven women, two men; mean age, 38 years; age range, 21–48 years) underwent the same MR imaging and MR spectroscopy procedures. The volunteers were enrolled on the basis of (a) negative answers to a health questionnaire administered prior to imaging and (b) normal interpretations of brain MR images according to two neuroradiologists (J.H. and R.I.G., with 5 and 25 years of experience, respectively). Our study was approved by our institutional review board, and all subjects gave informed consent.

MR Imaging and Proton MR Spectroscopy
MR imaging and three-dimensional proton MR spectroscopy were performed with a 1.5-T imager (Magnetom 63SP; Siemens, Erlangen, Germany). Contiguous transverse, sagittal, and coronal T1-weighted spin-echo (repetition time msec/echo time msec, 450/15) and transverse T2-weighted dual spin-echo (2500/16, 90) MR images were acquired. Other paramaters were section thickness, 7.5 mm; field of view, 240 x 240 mm; and data matrix, 256 x 256. An automatic shim procedure consistently yielded 9.0 Hz ± 1.0 (full width at half maximum) whole-head water lines. Proton MR spectroscopic images were acquired with a three-dimensional sequence, comprising 8th-order Hadamard encoding in the inferior-superior direction and 16 phase-encoding steps along the left-right and anteroposterior directions (14). Other parameters were 1600/135 and field of view of 8 (left-right) x 10 (anteroposterior) x 6 (inferior-superior) cm. This resolution yielded 8 (left-right) x 10 (anteroposterior) x 8 (inferior-superior) cm = 640 voxels, 0.75 cm3 each, in the volume of interest (Fig 1). The entire protocol took less than 80 minutes.



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  		Figure 1. A, Transverse T2-weighted (2500/90) MR image in a 26-year-old woman with MS. B, Transverse T1-weighted (450/14) MR image. C, Coronal T1-weighted (450/14) MR image. MR spectroscopic volume of interest has been superimposed on the images. Spectra from hypo- (arrows 1 and 4) and isointense (arrows 2 and 5) lesions, as well as two normal-appearing white-matter regions (arrows 3 and 6), are shown below the images on common intensity and chemical shift (in parts per million) scales. D-F, Corresponding sections from a matched control subject. Numbered arrows indicate equivalent regions to A-C for metabolite levels and spectra comparisons.

 
MR imaging and proton MR spectroscopic data were processed off-line. Residual water and lipid signals were removed in the time domain, 1-Hz lorentzian apodization was applied, and the data were zero-filled from 1024 to 2048 time points (15,16). The 16 (anteroposterior) x 16 (left-right) MR spectroscopic matrices were zero filled to 32 x 32, and the localization grid was aligned with the NAA volume of interest (17). Additional small voxel shifts were made by a neuroradiologist (J.H.) in the patient to optimize the grid over lesions, if necessary (17). Finally, the data were reconstructed along the three spatial directions and one spectral direction. They were automatically frequency aligned and were zero- and first-order phase corrected according to reference to the NAA and Cho peaks in each voxel (14).

Lesion Selection and Characterization
Since acute hypointensity on T1-weighted MR images is often transient (7,18), only persistent lesions—those which had been visible on T2-weighted MR images at least 6 months earlier—were examined, as suggested by Barkhof et al (18). Hyperintense lesions on T2-weighted MR images were classified by a neuroradiologist (J.H.) according to the average signal intensity on the corresponding T1-weighted MR images. First, the standard deviation of the white matter signal intensity was found in a region of interest in adjacent normal-appearing white matter. Lesions that had a signal intensity of 2 standard deviations more than or were darker than the surrounding normal-appearing white matter were classified as hypointense; those within 2 standard deviations were classified as isointense. Finally, a neuroradiologist (J.H.) selected from each tissue (hypo- or isointense lesions and normal-appearing white matter in patients and analogous normal white matter in control subjects) one representative 0.75-cm3 voxel.

Metabolite Quantification
The relative levels of the jth metabolite (j = NAA, Cr, or Cho) in the ith voxel (i = 1, ... , 640) were calculated from their peak areas, Sij, by using the parametric spectral modeling and least-squares optimization method of Soher et al (19). The Sij values were converted to absolute concentrations, Qij (expressed in millimoles per liter), by means of phantom replacement with a 3-L sphere of 10.9 mmol/L NAA in water and scaling (20):

{r05ja26e01}
where Sij(s) and Sij(p) are the peak metabolite areas in the human subject and the phantom, respectively. Vs180° and Vp180° are the voltages into the 50-{Omega} coil required for a nonselective 1-msec 180° inversion pulse on each, reflecting their relative "receive" sensitivity (21).

The Qij from Equation (1) was corrected for different in vitro NAA levels: T1vitro/T2vitro = 1.4/0.75 seconds; and reports for in vivo, T1vivo/T2vivo = NAA, 1.4/0.43 seconds; Cr, 1.6/0.21 seconds; and Cho, 1.2/0.36 seconds (8,22–24),

{r05ja26e02}
This calculation ignores possible regional and tissue T1/T2 variations (23,24). However, we do not believe that this will significantly affect the results, since (a) we compared voxels in similar anatomic positions and (b) for 90° nutation at a repetition time of 1.2 · T1, the signal is relatively insensitive to T1 differences, with a change of ±20% in T1 giving only a ±5% change in signal (25).

To avoid partial cerebrospinal fluid volume effects, only voxels completely within a lesion or normal-appearing white matter, with no apparent ventricular or sulcal involvement, were considered. No correction was made for possible increased extracellular water, however, such as that described by Helms (26), since this effect is small in chronic lesions.

Statistical Analyses
All statistical analyses were performed with SAS System software, version 9.0 (SAS Institute, Cary, NC). Mixed-model analysis of covariance was used to compare tissue groups (hypo- and isointense lesions, normal-appearing white matter, and normal white matter in control subjects) with respect to metabolite concentrations, adjusting for differences attributable to between-subject variations in instrumental sensitivity not accounted for by the voltage correction in Equation (1).

A separate univariate analysis was conducted for each metabolite by using the levels observed for that metabolite over all 171 voxels as the dependent variable, with the statistical model including tissue type (hypointense lesion, isointense lesion, normal-appearing white matter, normal white matter in control subjects) as a fixed classification factor. The correlation structure introduced by the acquisition of multiple data points per subject was modeled by assuming that model error terms associated with either the same or different subjects are exchangeable or independent, respectively, while allowing the underlying variation in response to vary between tissue groups.

Within this mixed-model framework, the Tukey honestly significant difference procedure was used to make all pairwise comparisons among the four tissue types, while maintaining the familywise type I error rate at or below the nominal 5% level. Additionally, the model coefficient of determination, or R2, from a mixed-model analysis to predict each metabolite as a function of average signal intensity was used as the basis for assessment of correlations between (a) the metabolites and the average signal intensity among hypointense lesions and (b) the NAA and the average signal intensity from all tissues types. The percentage difference between the concentrations (NAA, Cr, and Cho) in pairs of tissue groups were expressed as a percentage of the reference group in the comparison. Results were declared significant at the Tukey honestly significant difference–corrected 5% level—that is, P values were significant at the 5% level after correction for multiple hypothesis tests.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 REFERENCES
 
Sixty-six hyperintense lesions on T2-weighted MR images fulfilled the selection criteria described earlier. Of these, 43 were hypointense and 23 were isointense on T1-weighted MR images. In addition, 31 lesion-free regions were selected in contralateral normal-appearing white matter, and 74 were selected in similar regions in normal white matter in control subjects, as shown in Figure 1. Average signal intensities were 88.2 ± 8.5 in normal white matter in control subjects, 81.5 ± 5.0 in normal-appearing white matter, 77.8 ± 4.3 in isointense lesions, and 70.3 ± 6.7 in hypointense lesions. Average signal intensity values were normalized by dividing each individual average signal intensity value by the average of all 31 normal-appearing white matter samples from all patients. Consequently, the average normalized signal intensity of normal-appearing white matter is 100%.

The metabolite concentrations of the tissue types studied are compiled in Table 1. Pairwise comparisons are shown in Table 2, and concentration distributions for each tissue type are presented as box plots in Figure 2. Specifically, in hypointense lesions, the mean NAA level (5.30 mmol/L ± 2.27) was lower than that in isointense lesions (7.82 mmol/L ± 2.28, P = .002), normal-appearing white matter (7.37 mmol/L ± 1.71, P < .001), and normal white matter in control subjects (8.89 mmol/L ± 1.54, P < .001).


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  		TABLE 1. Metabolite Concentrations in Four Tissue Types Examined

 

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  		TABLE 2. Pairwise Relationship between Average Metabolic Tissue Concentrations

 


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  		Figure 2. Box plots display the 25%-75% values (boxes) ± 95% values (whiskers), median values (horizontal lines within boxes), and outliers (*) of NAA, Cr, and Cho absolute level distribution within normal white matter in control subjects (NWM) and normal-appearing white matter (NAWM), isointense lesions (ISO), and hypointense lesions (HYPO) in patients with relapsing-remitting MS. Note lower-median NAA in hypointense lesions and higher Cr and Cho levels in normal-appearing white matter and isointense lesions.

 
Cho (1.79 mmol/L ± 0.65) and Cr (5.64 mmol/L ± 1.50) levels in isointense lesions were indistinguishable from those in normal-appearing white matter (1.74 mmol/L ± 0.46 and 4.99 mmol/L ± 0.97, respectively, but these levels were 20% and 24% higher than those in normal white matter in control subjects, respectively: 1.44 mmol/L ± 0.40 (P = .008) and 4.30 mmol/L ± 1.32 (P < .001). The NAA, Cho, and Cr levels in the normal-appearing white matter were 20% lower (P = .06), 14% higher (P < .006), and 17% higher (P < .001), respectively, than those in normal white matter in control subjects.

The NAA concentration was also plotted against the normalized average signal intensity in lesions, normal-appearing white matter, and normal white matter in control subjects in Figure 3. The least squares regression line is determined with the following equation: NAA level = (0.034 + 0.093) · AI, which indicates that the NAA level (expressed in millimoles per liter) increases by about 0.09 mmol/L per percentage of average signal intensity (AI). Within hypointense lesions alone, the average signal intensity did not correlate with NAA, Cr, or Cho levels.



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  		Figure 3. NAA level versus average signal intensity of tissue, expressed as percentage of average intensity (AI) of normal-appearing white matter (NAWM). The least squares regression line indicates a significant linear relationship: NAA level (expressed in millimoles per liter) = (0.034 + 0.093) · AI; that is, average 0.09 mmol/L increment of NAA level per 1% increment of average intensity. NWM = normal white matter in control subjects.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
REFERENCES
 
Because of limitations in the number of regions imaged, single-voxel and two-dimensional MR spectroscopy studies can focus on one or a few visible plaques in relatively small (<100 cm3) volumes (13,27). Three-dimensional proton MR spectroscopy allows the collection of more voxels from larger volumes. Here, quantitative metabolic measurements were obtained from approximately 0.5 L. Furthermore, the use of smaller voxels and grid shifting allowed us to minimize partial volume contamination of lesions with normal-appearing white matter and vice versa.

At an echo time of 135 msec, NAA, Cho, and Cr are quantifiable. NAA is considered the best surrogate marker for the density and integrity of axons and neurons, in which NAA is found almost exclusively (28). Its decrease in lesions and normal-appearing white matter has correlated with clinical disability (29). Cr is present in all cell types, but cell culture experiments have shown higher concentrations in astrocytes and oligodendrocytes than in neurons (30). Since Cr and phosphocreatine constitute the high-energy reserves of a cell, an increase of Cr could indicate demand from gliosis and/or remyelination (24). Finally, Cho, also present in all cells, is considered a marker of membrane turnover, and higher levels have been reported in normal-appearing white matter and acute and chronic MS lesions (31,32).

Hypointense Lesions on T1-weighted MR Images
First described by Uhlenbrock and Sehlen (33), hypointense lesions on T1-weighted MR images were considered foci of severe tissue damage. Biopsy (12) and postmortem histopathologic findings (6,34) demonstrated axonal loss and gliosis. MR imaging studies have corroborated these findings, showing that (a) hypointensity correlates with axonal density; (b) longer T1s correlate with both lower NAA levels, which is indicative of neuronal loss, and lower magnetization transfer ratios, which is indicative of demyelination; and (c) hypointensities exhibit higher mean diffusivity and lower fractional anisotropy, which are both markers of tissue destruction, on diffusion-weighted MR images (6,34–37).

The general reduction in all metabolite levels observed in these lesions therefore probably reflects tissue loss. That Cho and Cr levels decrease less than NAA level may be due to ongoing disease activity in the remaining tissue. This may explain, in part, why the correlation between hypointensity and metabolite levels seen in secondary progressive MS (6,34) was not observed in relapsing-remitting MS and, further, why T1-lesion loads correlate well with expanded disability status scale score in secondary progressive MS (35) but weakly at best in relapsing-remitting MS (35,38,39).

These findings are consistent with MR imaging and MR spectroscopy reports of variable damage patterns in lesions on T1-weighted images. This variability suggests that loss of normal tissue may be accompanied by gliosis (increased Cr level) or some remyelination (higher Cho and Cr levels) (5–10). This hypothesis is corroborated by a longitudinal study (40) showing slight but significant increases of the (strongly decreased) basal magnetization transfer ratio in hypointense nonenhancing lesions over a year.

Isointense Lesions at T1-weighted MR Imaging
About half of new contrast-enhanced MS lesions will become isointense on T1-weighted MR images (7). This recovery could result in part from resolved edema and inflammation (26). However, the high Cho and Cr levels found in the present study of chronic isointense lesions suggest abnormal metabolic activity long after the edema resolved. The similar NAA levels in these lesions and normal-appearing white matter could indicate either a mild pathologic insult or partial repair. Finally, increased Cho and, in particular, Cr levels may be related to attempted remyelination. This is consistent with results in a previous study (10), which showed that remyelination led to less hypo- and even isointensity over time. While higher Cr levels could also result from glial proliferation, this structurally disorganized process should lead to more, not less, hypointensity. Therefore, although caution must be taken in a cross-sectional study, Cr might be a potential marker for remyelination.

Normal-appearing White Matter
The lower NAA and higher Cr and Cho levels in normal-appearing white matter compared with those in normal white matter in control subjects are in agreement with previous MR spectroscopic findings, postmortem findings, and biopsy reports of axonal loss in normal-appearing white matter (3,41–43). Without follow-up, however, reversibility of NAA losses cannot be ruled out (44). The increase of Cr and Cho levels in normal-appearing white matter relative to normal white matter in control subjects is more controversial, since previous proton MR spectroscopy studies have yielded variable patterns, ranging from significant increases to parity (32,41,45). Increased levels could indicate parallel de- and remyelination, gliosis, and inflammation. On the basis of our data, however, we can only speculate on the structural correlate of our findings, since abnormalities other than axonal injury have been described in normal-appearing white matter—such as diffuse astrocytic hyperplasia, patchy edema, perivascular cellular infiltration, and abnormally thin myelin sheaths (43). Nevertheless, our findings indicate that metabolic abnormalities in relapsing-remitting MS are present everywhere in the normal-appearing white matter and are not confined to just the enhancing lesions (46).

These conclusions are subject to a few caveats because of limitations of our methods. First, since the patients were not recruited prospectively, our selection criteria could have introduced some bias. Second, use of 7.5-mm-thick MR imaging and MR spectroscopy sections may have favored thicker lesions over thinner ones, which would not fill a section. Third, since tissue samples were not available, our MR spectroscopy findings could not be corroborated directly against histopathologic findings. Fourth, our 135-msec echo time, although instrumental in yielding a flatter baseline and better lipid suppression, precluded quantification of J-coupled species—such as myo-inositol. A more definite marker or gliosis and increased myo-inositol and Cr levels could have helped arbitrate between that process and remyelination.

Monitoring of several tissue types and regions with three-dimensional proton MR spectroscopy showed that (a) while none of the lesions enhanced (the current radiologic surrogate of activity), all had abnormally increased Cho and Cr levels. Enhancement alone may therefore lead to underestimation of overall activity. (b) Isointense lesions showed the highest Cho and Cr levels. Since histopathologic findings have associated remyelination with less hypointensity at T1-weighted MR imaging, this observation may reflect repair. (c) Normal-appearing white matter with increased Cho and Cr levels is not quiescent, either. These observations suggest that metabolic abnormalities persist in lesions and in normal-appearing tissue, even during periods of clinical quiescence and lack of current radiologic (MR imaging) surrogates of activity.


   FOOTNOTES
 
Abbreviations: Cho = choline, Cr = creatine, MS = multiple sclerosis, NAA = N-acetylaspartate

Authors stated no financial relationship to disclose.

Author contributions: Guarantor of integrity of entire study, O.G.; study concepts and design, R.I.G., O.G.; literature research, J.H., M.I., R.I.G., O.G.; clinical studies, J.H., M.I., R.I.G.; experimental studies, B.S.Y.L., O.G.; data acquisition, B.S.Y.L., R.I.G., O.G.; data analysis/interpretation, all authors; statistical analysis, J.S.B.; manuscript preparation, J.H., M.I., J.S.B., O.G.; manuscript definition of intellectual content, J.H., M.I., R.I.G., O.G.; manuscript editing and revision/review, M.I., R.I.G., O.G.; manuscript final version approval, O.G.


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TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 

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