Abstract
Objectives: To quantify, using diffusion tensor imaging (DTI), the tissue damage in lesions and normal-appearing white matter (NAWM) from a large cohort of patients with MS and to investigate the magnitude of the correlation between DTI-derived metrics and clinical disability.
Methods: Dual-echo and DTI scans were obtained from 78 patients with relapsing-remitting, secondary progressive, or primary progressive MS and from 20 normal control participants. Post-contrast T1-weighted images were also obtained from the patients. After creating mean diffusivity () and fractional anisotropy (FA) images and image coregistration, and FA values were measured for 4846 lesions (3207 nonenhancing T1-isointense, 1511 nonenhancing T1-hypointense, and 128 enhancing), 497 NAWM areas from patients, and 160 white matter areas from the controls.
Results: The average lesion was higher and the average lesion FA was lower than the corresponding quantities of the NAWM (p < 0.001). The values of enhancing and nonenhancing lesions were not different, whereas enhancing lesions had lower FA (p < 0.001). T1-hypointense lesions had higher and lower FA than T1-isointense lesions (p < 0.001). NAWM of patients had higher and lower FA than white matter of controls (p = 0.01). Significant correlations were found between T1 and T2 lesion volume and and FA of lesions and NAWM. In the overall patient sample, a moderate correlation was also found between lesion and the Expanded Disability Status Scale score (r = 0.28, p = 0.01). However, the r value of this correlation was 0.48 in patients with secondary progressive MS, whose disability was also correlated with average lesion FA (r = −0.50).
Conclusions The results of this study show that DTI is able to identify MS lesions with severe tissue damage and to detect changes in the NAWM. They also indicate that DTI-derived measures are correlated with clinical disability, especially in patients with secondary progressive MS, thus suggesting a role for DTI in monitoring advanced phases of the disease.
Diffusion is the microscopic random translational motion of molecules, and water molecular diffusion can be measured in vivo using diffusion-weighted MRI (DW-MRI).1 Because diffusion is affected by the properties of the medium where molecular motion occurs,2 measurement of diffusion inside biologic tissues provides information about tissue structure at a microscopic level.3 The motion of water molecules can be hindered by the presence of structural barriers at a cellular or subcellular level. Pathologic processes that alter tissue organization by decreasing or increasing the number of barriers to water molecular motion, or that alter the permeability of the barriers, cause abnormal water diffusivity. In addition, diffusion is inherently a three-dimensional process, and in some tissues with an oriented microstructure, such as brain white matter, the molecular mobility is not the same in all directions. This property is called anisotropy, and it results in a variation in the measured diffusivity with tissue measurement direction.4-5⇓ White matter fiber tracts consist of aligned myelinated axons, and, therefore, hindrance of water diffusion is much greater across rather than along the major axis of axonal fibers.6 Under these conditions, a full characterization of diffusion can only be found in terms of a tensor,7 a 3 × 3 matrix, where the on-diagonal elements represent the diffusion coefficients along the axes of the reference frame, whereas the off-diagonal elements account for the correlations between molecular displacement along orthogonal directions. From the tensor, it is possible to derive some scalar indices, invariant to the changes in the frame of reference, that reflect the diffusion characteristics of the tissue. These measures include 1) the mean diffusivity () (equal to one third of the trace of the diffusion tensor), which is a measure of the average molecular motion independent of any tissue directionality and is affected by cellular size and integrity8-9⇓; and 2) the fractional anisotropy (FA), which is one of the most commonly used measures of deviation from isotropy9 and reflects the degree of alignment of cellular structures within fiber tracts, as well as their structural integrity.
Although DW-MRI has been shown to be of great clinical utility in the assessment of patients with cerebral ischemia,10-11⇓ its application to other neurologic conditions has been limited. This technique seems like a promising tool for the quantification of tissue damage and for improving our understanding of conditions that affect the integrity and organization of brain tissues. The pathologic elements of MS have the potential to alter the permeability or geometry of structural barriers to water molecular diffusion in the brain. Consistent with this, results of preliminary studies12-15⇓⇓⇓ found that water diffusivity in MS lesions is higher than in normal-appearing white matter (NAWM), where water diffusivity is, however, higher than in white matter of healthy volunteers. Although these preliminary studies were affected by limitations of the MRI techniques used—namely motion artifacts and long data acquisition time that prevented extensive brain coverage—their results were confirmed by more recent studies16-18⇓⇓ that used echoplanar imaging (EPI) technology, which is less prone to motion and permits greater brain coverage, with more diffusion gradient directions, in a given time. However, only one study applied diffusion tensor imaging (DTI) in six patients with relapsing-remitting (RR) or secondary progressive (SP) MS.16 In the current study, we used DTI to quantify tissue damage in NAWM and lesions with different appearances on conventional MR images from a large cohort of patients with the three major MS clinical phenotypes. We also investigated the magnitude of the correlation between DTI and conventional MRI changes and between MRI- and DTI-derived measures and clinical disability.
Patients and methods.
Patients.
We studied 78 patients with MS (42 women and 36 men). Their mean age was 41.6 years (SD = 9.5 years), median duration of the disease was 10 years (range = 1 to 28 years), and median Expanded Disability Status Scale (EDSS) score19 was 5.0 (range = 0.0 to 8.5). According to the criteria of Lublin and Reingold,20 28 of the patients were classified as having RR, 20 as having SP, and 30 as having primary progressive (PP) MS ( table 1). When MRI scans were obtained, none of the patients with RRMS or SPMS was experiencing an acute relapse nor were they being treated with corticosteroids. Twenty healthy volunteers (12 women and 8 men; mean age = 37.2 years, SD = 9.2 years) with no history of neurologic disorders and a normal neurologic examination served as controls. Local Ethical Committee approval and written informed consent from all the subjects were obtained before study initiation.
Demographic, clinical, and conventional MRI characteristics of controls and patients with three different MS clinical phenotypes
Image acquisition.
The following sequences were obtained from all the subjects during a single imaging session using a 1.5 T scanner (Siemens Vision, Erlangen, Germany):
1) Dual-echo turbo spin echo (TSE) (repetition time [TR] = 3300, first echo echo time [TE] = 16, second echo TE = 98, echo train length = 5).
2) Pulsed-gradient spin-echo echoplanar pulse sequence (interecho spacing = 0.8, TE = 123), with diffusion gradients applied in eight noncolinear directions, chosen to cover three-dimensional space uniformly.21 The duration and maximum amplitude of the diffusion gradients were 25 msec and 21 mTm−1, giving a maximum b factor in each direction of 1044 seconds mm−2. To optimize the measurement of diffusion, only two b factors were used22 (b1 ≈ 0, b2 = 1044 seconds mm−2). Fat saturation was performed using a four radiofrequency (RF) pulse binomial pulse train to avoid the chemical shift artifact. A bird-cage head coil of ∼300 mm diameter was used for RF transmission and for signal reception.
3) T1-weighted conventional SE (TR = 768, TE = 15) 5 minutes after the injection of 0.1 mmol/kg of gadolinium-DTPA.
For the dual-echo and T1-weighted scans, 24 contiguous interleaved axial slices were acquired with 5 mm slice thickness, 256 × 256 matrix, and 250 × 250 mm field of view. The slices were positioned to run parallel to a line that joins the most infero-anterior and infero-posterior parts of the corpus callosum.23 For the DW scans, 10 axial slices with 5 mm slice thickness, 128 × 128 matrix, and 250 × 250 mm field of view were acquired, with the same orientation of the dual-echo scans, with the second-last caudal slice positioned to match exactly the central slices of the dual-echo and T1-weighted sets. This brain portion was chosen because the periventricular area is a common location for MS lesions. In addition, these central slices are less affected by the distortions caused by B0 field inhomogeneity, which can affect image coregistration.
Image analysis and postprocessing.
All image postprocessing was performed on a computer workstation (Sun Sparcstation; Sun Microsystems, Mountain View, CA) separate from the scanner. DW images were first corrected for distortion induced by eddy currents using an algorithm that minimizes mutual information between the diffusion unweighted and weighted images.24 Then, assuming a mono-exponential relation between signal intensity and the product of the b-matrix (a 3 × 3 matrix that expresses the relation between signal attenuation and elements of the diffusion tensor matrix) and diffusion tensor matrix components, the diffusion tensor was calculated for each pixel according to the following equation:equation 
where M is the measured signal intensity, M0 is the T2-weighted signal intensity, bij are the elements of the b matrix, and Dij are the elements of the diffusion tensor matrix. The tensor was estimated by nonlinear regression using the Marquardt–Levenberg method. After diagonalization of the estimated tensor matrix, the two scalar invariants of the tensor, ¯ and FA, were derived for every pixel ( figure 1). The diffusion images were interpolated to the same image matrix size as the dual-echo, and then the b = 0 step of the EPI scans (T2-weighted, but not diffusion weighted) was coregistered with the dual-echo T2-weighted images using a three-dimensional rigid-body coregistration algorithm based on mutual information.24 Characteristics of this algorithm are described in detail elsewhere.24 Accuracy of the registration was confirmed by overlaying contours of the outline of the brain and the ventricles, measured on the dual-echo images, on the b = 0 EPI. Figure 2 shows a typical example of this procedure, indicating how well the registration worked. The same transformation parameters were then used to coregister the D and FA images to the dual-echo and T1-weighted images.
Figure 1. Axial MR images obtained from a patient with relapsing-remitting MS (RRMS). The proton-density weighted scan (A) shows multiple lesions. The T1-weighted scan (B) shows that some of these lesions are enhancing (in one, ring-enhancement is visible), whereas others are hypointense relative to the normal-appearing white matter. On the mean diffusivity (D) image (C), lesions appear as hyperintense areas compared with the surrounding tissue. The degree of hyperintensity is related to increase in D and indicates a loss of structural barriers to water molecular motion. On the fractional anisotropy (FA) image (D), white matter pixels are bright because of the directionality of white matter fiber tracts. Dark areas corresponding to macroscopic lesions indicate a loss of FA and suggest the presence of white matter structural disorganization.
Figure 2. Conventional turbo spin-echo T2-weighted image (A) and coregistered b = 0 echoplanar image from the diffusion-encoding data set (B) from a healthy control participant. The outlines of the brain and the ventricles, measured as contours on the turbo spin-echo image, are superimposed onto the echoplanar image, confirming the accuracy of the registration procedure.
Lesions were identified on the proton-density (PD) weighted scans and marked on the hard copies by two observers, unaware of the patients’ clinical status, by agreement. T2-weighted images were always used to increase confidence in lesion identification. To minimize partial volume effects, only lesions with a diameter greater than 5 mm entered the subsequent analysis. Using postcontrast T1-weighted scans, these lesions were classified as enhancing or nonenhancing, according to previously published criteria.25 Nonenhancing lesions were classified as T1-isointense or hypointense. T1 hypointensity was defined as reduced lesion signal intensity with respect to surrounding NAWM. Then, a single observer, unaware of lesion classification, displayed the dual-echo images on a computer screen and, using marked hard copies as a reference, outlined these lesions on the PD-weighted images and measured lesion volumes using a semi-automated segmentation technique based on local thresholding.26 The outlined regions of interest (ROI) were automatically transferred onto the coregistered ¯ and FA images, and the area ¯ and FA of each lesion was measured. Then, for each patient the averaged ¯ and FA (for all lesions, enhancing lesions, nonenhancing lesions, T1-isointense lesions, and T1-hypointense lesions), weighted by lesion area,26 were calculated.
¯ and FA values of NAWM in different brain regions were also studied. The NAWM areas were selected on the dual-echo scans so that they had no adjacent lesions either in the same slice or in the slices above and below. Whenever possible, square ROI of uniform size (3 × 3 pixels) were placed bilaterally in the white matter of the following areas: the genu and the splenium of the corpus callosum, the internal capsules, adjacent to the anterior and posterior parts of the body of the lateral ventricles, and in the frontal lobe. The outlined NAWM regions were then transferred onto the coregistered ¯ and FA images and the average values calculated. Using the same method, ¯ and FA of the same brain regions were measured from controls.
Intraobserver reproducibility of DW-MRI measures from lesions and NAWM was also assessed. On two separate occasions (separated by at least 4 months), the same observer measured ¯ and FA of 60 randomly selected lesions (20 T1-isointense, 20 T1-hypointense, and 20 enhancing) and of the above-mentioned NAWM areas from 10 randomly selected patients. The mean intraobserver coefficients of variation for ¯ and FA were lower than 1.5% for all the tissue types studied.
Statistical analysis.
A Student’s t-test for nonpaired data was used to compare 1) ¯ and FA values from the ROI placed in the NAWM from patients with those of the corresponding ROI placed in the white matter from controls; 2) ¯ and FA values in the NAWM from patients with those of lesions; 3) ¯ and FA values of enhancing lesions with those of nonenhancing lesions; and 4) ¯ and FA values of T1-isointense with those of T1-hypointense lesions. Pairwise comparisons between controls and each of the MS clinical phenotypes and among RRMS, SPMS, and PPMS were all performed using the same test. To correct for the multiple comparisons and to minimize the risk of type II errors, only p values ≤ 0.01 were considered significant. Univariate correlations were assessed using the Spearman rank correlation coefficient.
Results.
Conventional MRI.
No abnormalities were seen on any of the conventional MRI scans obtained from controls. In the overall MS population, the median T2 lesion volume was 18.7 mL (range = 0.4 to 106.9 mL), the median T1-hypointense lesion volume 4.2 mL (range = 0.0 to 50.5 mL), and the median number of enhancing lesions 0 (range = 0 to 15). In table 1, these MR quantities are reported separately for each of the clinical phenotypes.
DW-MRI characteristics of NAWM.
A total of 160 white matter ROI from controls and 497 NAWM ROI from MS patients were studied. In table 2, the average ¯ and FA values for all the white matter and NAWM regions studied are reported. The average ¯ of NAWM from patients was higher (p = 0.01) and the average FA lower (p = 0.01) than the corresponding quantities from white matter in controls. When different white matter and NAWM regions were considered in isolation, significant differences in ¯ and FA values were found for the periventricular (p < 0.001) and frontal lobe (p < 0.001) white matter. ¯ and FA of the NAWM from patients were moderately correlated (r = −0.4, p < 0.001) ( figure 3).
Mean diffusivity (¯) and fractional anisotropy (FA) in different white matter areas from controls and patients with MS
Figure 3. Scatterplots of the average mean diffusivity (¯) versus the average fractional anisotropy (FA) for MS lesions (A) and normal-appearing white matter (B).
DW-MRI characteristics of MS macroscopic lesions.
A total of 4846 lesions were seen on the dual-echo scans. Their average ¯ was 1.06 ± 0.23 × 10−3 mm2s−1, and average FA was 0.26 ± 0.09. These values were both different (p < 0.001) from those of the NAWM (¯ = 0.86 ± 0.15 × 10−3 mm2s−1; FA = 0.38 ± 0.16). In table 3, the average ¯ and FA values for each type of macroscopic MS lesion studied are reported. A total of 128 enhancing lesions were studied (only one of them was ring-enhancing; see figure 1). Average ¯ values of enhancing and nonenhancing lesions were not significantly different, whereas the average FA of enhancing lesions was lower than that of nonenhancing lesions (p < 0.001). The number of nonenhancing lesions classified as T1-hypointense was 1511. They had increased ¯ and decreased FA compared with the remaining 3207 T1-isointense lesions (p < 0.001). An inverse correlation between average lesion ¯ and FA was found (r = −0.6, p < 0.001) (see figure 3).
Mean diffusivity (¯) and fractional anisotropy (FA) of different MS lesion types
DW-MRI characteristics in the different MS clinical phenotypes.
¯ and FA values of MS lesions and NAWM were not significantly different between the three clinical phenotypes studied (data not shown). As shown for the entire patient sample, each of the three clinical phenotypes had average ¯ and FA values of all the NAWM regions and of periventricular and frontal lobe NAWM different from those of controls (p values ranging from <0.001 to 0.01). In addition, patients with PPMS also had increased ¯ in the corpus callosum (average ¯ = 1.06 ± 0.15 × 10−3 mm2s−1; p = 0.01) and decreased FA in the internal capsule (average FA = 0.34 ± 0.07; p = 0.005) compared with the same areas in controls.
Correlations between DW-MRI and conventional MRI findings.
Both T2-hyperintense (r = 0.6, p < 0.001) and T1-hypointense (r = 0.7, p < 0.001) lesion volumes were correlated directly with average lesion ¯ and inversely with average lesion FA (r = −0.6, p < 0.001 for both). T2-hyperintense and T1-hypointense lesion volumes were also correlated, albeit less strongly, with average NAWM ¯ (r = 0.5, p < 0.001 for T2 and r = 0.4, p < 0.001 for T1) and FA (r = −0.3, p < 0.001 for T2 and r = −0.2, p < 0.001 for T1).
Correlations between MR quantities and EDSS.
In the entire MS sample, T2 lesion volume (r = 0.22, p = 0.05), T1 lesion volume (r = 0.34, p = 0.002), and average lesion ¯ (r = 0.28, p = 0.01) ( figure 4) were correlated with the EDSS score. When the different MS phenotypes were considered in isolation, significant correlations between the EDSS score and average lesion ¯ (r = 0.48, p = 0.03) and FA (r = −0.50, p = 0.03) were found only for patients with SPMS. In these patients, EDSS score was not significantly correlated with T2 and T1 lesion volumes, whereas this was the case for patients with RRMS (T2 lesion volume: r = 0.41, p = 0.03; T1 lesion volume: r = 0.50, p = 0.01). In patients with RRMS, no significant correlations were found between EDSS score and average lesion ¯ and FA. No significant correlation was found between EDSS and DW-MRI metrics of NAWM in the entire MS sample and in each of the three clinical phenotypes when considered in isolation.
Figure 4. Scatterplots of the average lesion mean diffusivity (¯) versus the Expanded Disability Status Scale (EDSS) score from patients with relapsing-remitting MS (A), secondary progressive MS (B), primary progressive MS (C), and the overall patient sample (D).
Discussion.
DTI is able to probe structural properties of tissue (including size, shape, integrity, and orientation of water-filled spaces) that are inaccessible to other MRI techniques.1-9⇓⇓⇓⇓⇓⇓⇓⇓ The different pathologic elements of MS can alter the permeability or geometry of structural barriers to water diffusion in the brain. As a consequence, DTI might provide quantitative information about the structural damage occurring in MS lesions and NAWM that is complementary to that provided by other MR techniques; DTI therefore has the potential to increase our understanding of MS pathophysiology. Only one previous preliminary study16 applied DTI in MS patients. Six patients were examined (five with RRMS and one with SPMS), and, therefore, the relation between DTI changes and clinical course or level of disability was not investigated. Neither did it provide a systematic assessment of DTI changes in NAWM of different brain structures. In the current study, we measured ¯ and FA values in different NAWM areas and lesions with different degrees of pathologic damage and inflammatory activity. Because this study was conducted with a large cohort of patients with the three main MS phenotypes, this allowed, on the one hand, previous observations to be confirmed and, on the other, an assessment of the potential of ¯ and FA to characterize MS-related tissue damage. We were also able to evaluate clinical correlations.
¯ and FA values are highly variable in MS lesions and different from those in NAWM. This indicates that variable degrees of tissue damage occur within MS lesions and confirms the results of previous studies.12-17⇓⇓⇓⇓⇓ We found that nonenhancing T1-hypointense lesions had greater ¯ and lower FA values than T1-isointense lesions. Results of previous studies showed that T1-hypointense lesions are those where severe tissue loss has occurred27,28⇓ and where the extent is correlated with disease progression in patients with SPMS.29 Although postmortem studies correlating histopathology and DTI changes are needed, this observation shows the potential for DTI to provide quantitative metrics for monitoring tissue damage in MS.
Results of a previous 6-month follow-up study30 showed that 80% of the newly formed MS lesions are hypointense on unenhanced T1-weighted scans and 44% of them return to isointensity during the course of the follow-up, suggesting a variable effectiveness of reparative mechanisms. Interestingly, we found that T1-isointense lesions had the highest FA values of all the lesion types studied. Because glial cells are fairly amorphous and glial proliferation is a rather structurally disorganized process31 and should reduce FA, whereas remyelination should result in the restoration of FA toward normality, our results prompt us to speculate that reduction of inflammation and remyelination might be the mechanisms leading to T1-isointense lesions or, conversely, that failure of repair might be the mechanism leading to lesions with irreversible tissue damage. Although longitudinal and histopathologic correlative studies are warranted to support this hypothesis, results of this study suggest that the combined use of DTI-derived measures have the potential to detect specific MS pathologic changes and to provide MR patterns of tissue damage and repair.
We also compared ¯ and FA in enhancing and nonenhancing MS lesions. Enhancing lesions reflect acute disease activity, and results of histologic studies have shown that they correspond to areas with increased blood–brain barrier permeability and are associated with edema, inflammation, demyelination, and axonal loss.32,33⇓ These processes are all likely to increase ¯ and to reduce FA. The accumulation of inflammatory cells and myelin breakdown products could potentially both restrict water diffusion and decrease FA because of the presence of nonoriented barriers to diffusion; however, this is likely to be a small effect because of their relatively low concentration. Our findings show that enhancing lesions have 1) an average ¯ in the range of that of nonenhancing (chronic) lesions (and higher than that of T1-isointense lesions) and 2) the lowest FA of all the other lesion types studied. This cross-sectional study cannot address the important issue of how much of this tissue disorganization is permanent (i.e., related to axonal loss) and how much is transient (i.e., related to edema, demyelination, and remyelination).
The results of this study also confirmed and extended preliminary observations that NAWM from patients with MS have higher ¯12-18⇓⇓⇓⇓⇓⇓ and lower FA16 than the white matter from controls. This is consistent with the findings of other pathologic, magnetization transfer imaging (MTI), DWI, and MR spectroscopy (MRS) studies, all showing that tissue damage occurs outside visible T2-weighted lesions.34 Although these results indicate a net loss and disorganization of structural barriers to water molecular motion in the NAWM, we can only speculate on the possible pathologic substrates of these findings. Subtle changes are known to occur in the NAWM of patients with MS, including diffuse astrocytic hyperplasia, patchy edema, perivascular infiltration, gliosis, abnormally thin myelin, and axonal loss.34 Although all these processes might reduce FA, myelin and axonal loss should lead to increased water diffusivity. As a consequence, we believe that they are the most likely contributors to the increased ¯ and decreased FA we observed in the NAWM. In addition to confirming previous observations,12-18⇓⇓⇓⇓⇓⇓ results of this study provide a systematic evaluation of different brain regions and indicate that NAWM changes in MS are widespread but tend to be more severe in sites such as the periventricular areas and frontal lobe white matter, where macroscopic MS lesions are usually located.
In our sample, ¯ and FA of lesions were strongly correlated with lesion extent on T2- and T1-weighted images. This provides support for the concept that, on average, the size of lesions and the severity of the tissue damage within them run parallel, suggesting that the formation of severely damaged lesions is an accumulative process and explaining the beneficial effect on persistent disability of those treatments able to suppress new lesion formation.35-37⇓⇓ We also found only a moderate correlation between ¯ and FA of NAWM and macroscopic lesion extent. This is consistent with previous MTI findings38 and suggests that subtle NAWM changes are not merely the result of Wallerian degeneration of axons transversing larger lesions.
Results of this study confirmed the presence of a significant correlation between ¯ and FA of macroscopic MS lesions,16 which was, however, far from being a strict relationship. Because tissue damage alone would both increase ¯ and decrease FA, this observation confirms the potential of serial DTI scans to monitor tissue repair. For example, marked glial proliferation would decrease both ¯ and FA in concert, thus reducing the magnitude of the correlation that would result from a marked preponderance of tissue damage over tissue repair.
The limited number of patients previously studied16 prevented the investigation of whether different MS phenotypes had different DTI changes in lesions and NAWM. The results of this study show that the DTI characteristics of lesions visible on conventional MR do not differ among the three phenotypes studied and that damage in the NAWM tends to be distributed similarly. It is intriguing, however, that the DTI measures in the internal capsules and corpus callosum NAWM were different between controls and patients with PPMS. Conventional MRI typically shows a few lesions in patients with PPMS,39 despite their having severe locomotor disability39 and cognitive impairment.40 The loss of structural barriers to water motion in the NAWM of the internal capsules and a loss of fiber organization in the NAWM of the corpus callosum that we found might, at least partially, explain the clinical manifestations in these patients.
Average ¯ was found to be significantly correlated, albeit moderately, with clinical disability. Such a correlation was not reported previously because of the small numbers of patients studied.12-18⇓⇓⇓⇓⇓⇓ The lack of a similar correlation between disability and FA indicates that the loss of overall impediment to diffusional motion is more important than the loss of tissue anisotropy in determining patients’ clinical status. This fits well with the concept that loss of anisotropy might also result from reparative mechanisms, and the significant decrease in FA in enhancing lesions may be caused by transient phenomena, such as vasogenic edema. However, the magnitude of the correlation between ¯ and disability was still disappointing. Several factors might explain this, including the many limitations of the EDSS score41 and the role of spinal cord damage in determining neurologic disability.42 Nevertheless, in patients with SPMS we found a moderate and significant correlation between average lesion ¯ or FA and the EDSS score, whereas no significant correlation was found between disability and T2 lesion volume. Interestingly, a significant correlation between disability and T2 lesion volume was found in patients with RRMS, whereas, in turn, there was no correlation between average lesion ¯ or FA and EDSS score. These findings suggest that mechanisms leading to disability are likely to be different in patients with RRMS and SPMS. Although caution must be exercised because this is a cross-sectional study, one might speculate that new lesion formation is a relevant pathologic aspect in RRMS, whereas tissue loss in pre-existing lesions is one of the pathologic hallmarks of SPMS. As a consequence, our results suggest that different MR quantities should be used to monitor the different phases of MS evolution and indicate DTI-derived measures as promising MR markers to be used in addition to conventional MRI to monitor the evolution of SPMS.
- Received June 15, 2000.
- Accepted October 3, 2000.
References
Disputes & Debates: Rapid online correspondence
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.