Correlates of MS disability assessed in vivo using aggregates of MR quantities
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Abstract
Objectives: To assess the magnitude of the correlations between disability and composite MRI scores in patients with MS.
Methods: T2- and T1-weighted MRI, magnetization transfer imaging, diffusion tensor imaging, and MRS imaging scans of the brain from 23 patients with MS were obtained. T2 lesion volume, T1 lesion volume, brain magnetization transfer ratio, average brain diffusivity (D), and brain N-acetylaspartate/creatine ratio were measured.
Results: The correlations between the Expanded Disability Status Scale (EDSS) score and each of the MR quantities taken in isolation were not significant, with the exception of the correlation between EDSS and the NAA/creatine ratio (r = −0.50; p = 0.01). In contrast, three of the composite MR scores computed using regression models were strongly correlated with the EDSS scores (r range, 0.58 to 0.73; p range, 0.004 to 0.0001). The model that included T2 and T1 lesion volumes and brain D explained 34% of the EDSS variance; the model that included T2 and T1 lesion volumes and brain N-acetylaspartate/creatine ratio explained 36% of the EDSS variance; the model that included T1 lesion volume, brain D, and brain N-acetylaspartate/creatine ratio explained 53% of the EDSS variance.
Conclusions: The results suggest that multiparametric MR models have the potential to provide powerful measures to monitor MS evolution.
Although T2-weighted MRI is sensitive for the detection of MS lesions, it lacks specificity with regard to their pathologic substrates and does not delineate tissue damage occurring in normal-appearing white matter (NAWM).1 These limitations can account for the poor correlation between disability and MRI findings in patients with MS.1
The limitations of T2-weighted MRI can be at least partially overcome by the use of other MR modalities. Information about the extent of lesions with severe intrinsic damage can be obtained by measuring the load of hypointense lesions on T1-weighted images.2,3⇓ Magnetization transfer imaging (MTI) and diffusion tensor imaging (DTI) provide additional quantitative information about the degree of structural change and tissue disorganization occurring in macroscopic MS lesions, NAWM, and large portions of the brain.4-8⇓⇓⇓⇓ Finally, 1H-MRS can add biochemical information about two of the major pathologic aspects of MS: the active inflammatory–demyelinating process and axonal injury.9-12⇓⇓⇓ Previous studies found encouraging correlations between these MR quantities and disability in MS.2,4,9-11⇓⇓⇓⇓ We anticipated that multiparametric MR models might provide more accurate pictures of tissue damage in MS than those derived from the application of individual MR techniques in isolation. Therefore, we obtained T2- and T1-weighted MRI, MTI, DTI, and MRS imaging (MRSI) scans of the brain from patients with MS to assess the magnitude of the correlation between clinical disability and aggregates of MR quantities thought to reflect different aspects of MS pathology.
Patients and methods.
Patients.
We studied 23 patients (17 women and six men), 21 of whom had relapsing-remitting and two secondary progressive MS.13 Their mean age was 37.1 years (SD, 8.9 years), median duration of the disease was 5 years (range, 1 to 21) and median Expanded Disability Status Scale (EDSS) score14 was 2.0 (range, 0.0 to 6.0). All patients were relapse- and steroid-free for at least 3 months before study entry; 15 of those with relapsing-remitting MS were being treated with interferon beta. On the day MRI scans were obtained, patients were assessed clinically by a single neurologist who was unaware of the MRI results. Local Ethical Committee approval and written informed consent from all the subjects were obtained before study initiation.
Image acquisition.
All patients underwent scanning on two occasions separated by an interval of about 72 hours. During the first session, several scans were obtained using a 1.5-T scanner. First, we performed dual-echo turbo spin echo (repetition time [TR], 3,300 ms; echo time [TE], 16/98 ms; echo train length, 5). Second, two-dimensional gradient echo (TR, 600 ms; TE, 12 ms; flip angle, 20°) with and without an off-resonance radiofrequency saturation pulse (offset frequency, 1.5 kHz; Gaussian envelope duration, 7.68 ms; flip angle, 500°) was done.
Third, pulsed gradient spin-echo single-shot echoplanar pulse sequence (PGSE-EPI) (interecho spacing, 0.8 ms; TE, 123 ms) was performed, with diffusion gradients applied in eight noncollinear directions, chosen to cover three-dimensional space uniformly.15 The duration and maximum amplitude of the diffusion gradients were 25 ms and 21 mTm−1 giving a maximum b factor in each direction of 1,044 s/mm2. In order to optimize the measurement of diffusion, only two b factors were used (b1 ≈ 0, b2 = 1,044 s/mm2). Fat saturation was performed using a four radiofrequency binomial pulse train to avoid a chemical shift artifact. A birdcage head coil of approximately 300-mm diameter was used for signal transmission and reception. Finally, T1-weighted conventional spin echo (TR, 768 ms; TE, 15 ms) was performed 5 minutes after injection of 0.1 mmol/kg gadolinium–diethylenetriaminepentaacetic acid.
For turbo spin echo, gradient echo, and conventional spin echo sequences, 24 contiguous axial slices were acquired (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 inferoanterior and inferoposterior parts of the corpus callosum. For PGSE-EPI scans, 10 axial slices (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-to-last caudal slice positioned to match exactly the central slices of the dual-echo, gradient echo, and T1-weighted sets. This brain portion was chosen because the periventricular area is a common location for MS lesions and these central slices are less affected by the distortions due to B0 field inhomogeneity.
During the second session, MRSI scans of the brain were obtained using another MR system operating at 1.5 T. A turbo spin echo sequence with axial slices parallel to the line connecting the anterior and posterior commissures was acquired. These images were used to select an intracranial volume of interest measuring approximately 90 mm (anteroposterior) × 20 mm (craniocaudal) × 90 mm (left to right), centered on the corpus callosum. Two-dimensional spectroscopic images were obtained using a 90°–180°–180° pulse sequence (TR, 2,000 ms; TE, 272 ms; field of view, 250 × 250 mm; phase encoding steps, 32 × 32, with one signal average per step), as previously described.14
Image analysis and postprocessing.
All image analysis and postprocessing was conducted by an experienced observer, unaware of the patients’ clinical characteristics. T2 and T1 lesion volumes were measured using a segmentation technique based on local thresholding.16 The two gradient echo images (with and without the saturation pulse) were first coregistered,17 and then MT ratio (MTR) images were derived pixel by pixel, as previously described.4 PGSE-EP images were first corrected for distortion induced by eddy currents.17 Then, the diffusion tensor was calculated for each pixel according to the equation described by Basser et al.18 After “diagonalization” of the matrix, mean diffusivity (D) was derived for every pixel. The diffusion maps were then interpolated to the same matrix as the dual echo images. Histograms of MTR and D maps were created as previously described.4,7⇓ For all the histograms, the average MTR and D values were calculated as well as the heights and locations of the peaks of the histograms. Postprocessing of the MRS images was performed as previously described.19 Metabolite resonance intensities of N-acetylaspartate (NAA), choline, and creatine were determined automatically from peak areas relative to a spline-corrected baseline. Results were expressed as the intravoxel ratios of NAA and choline to total creatine.
Statistical analysis.
Univariate correlations between MR measures and disability were assessed using the Spearman rank correlation coefficient. Multivariable linear regression models were used to generate composite MR scores. Each of these composite scores was computed using a linear combination of MR parameters, chosen a priori based on biologic considerations. The weight of each MR parameter resulted from the coefficients estimated by the regression model. The magnitude and the significance of the different correlations between EDSS and composite MR scores were evaluated by a nonparametric Spearman correlation analysis, because EDSS does not satisfy the assumptions of continuity and normality for a valid inference in linear regression models, and the sample size studied was too small for asymptotic properties to be applied.
Results.
Table 1 reports the means, medians, SD, and ranges for all MR quantities measured in this study. The mean percentages of pixels occupied by T2 lesions were as follows: 1.7% (range, 0.2% to 6.0%) of those included in MTR histogram analysis, 1.8% (range, 0.1% to 6.5%) of those included in D histogram analysis, and 2.2% (range, 0.1% to 7.0%) of those considered for MRSI measurements. Only the mean NAA/creatine ratio correlated with disability (r = −0.50; p = 0.01). A significance trend was observed for the mean peak height of the MTR histogram (r = −0.40; p = 0.06). None of the other univariate correlations reached significance. The r value of the correlation between T2 lesion volume and EDSS was 0.15.
Means, medians, SD, and ranges of the various MR quantities studied
Three composite models (A, B, and C) were then created using MR quantities reflecting different aspects of MS pathology. In all models, the first item was T2 lesion volume (reflecting the extent of macroscopic damage) and the second was T1 lesion volume (reflecting the amount of severely damaged lesions). The third item was brain D for model A, brain NAA/creatine ratio average for model B, and brain MTR for model C (all measures reflect the extent of overall damage in lesions and NAWM). Table 2 reports the r and p values of the correlations between the composite MR and the EDSS scores. Two models (A: T2 and T1 lesion volume plus brain D; and B: T2 and T1 lesion volume plus brain NAA/creatine ratio) allowed us to achieve significant correlations with disability. We then assessed the value of less demanding models by removing each of the factors included in both these models. Removal of T2 lesion volume from model A still resulted in a significant correlation between EDSS and composite MR scores (r = 0.60; p = 0.002). This was not the case when removing either T1 lesion volume (r = 0.29) or brain D (r = 0.23). For model B, the largest part of the correlation was accounted by the brain NAA/creatine ratio, because when either the T1 or T2 lesion volumes were removed, r values of the correlations were both 0.52 (p = 0.01). Therefore, we assessed the value of another model based on the two “best” parts of the two previous ones. This model included the T1 lesion volume, brain D, and brain NAA/creatine ratio. A strong correlation was found between the composite MR scores derived from this model and the EDSS scores (r = 0.73; p = 0.0001).
Correlations between the composite MR models and EDSS scores
Discussion.
Consistent with many other studies,1 we found that T2 lesion volume was not significantly correlated with disability and in fact explained only about 2.2% of the EDSS score variance in our patients. Also, no significant correlations were found between disability and many quantities derived from other MR techniques. This might be explained by the relatively small sample of patients studied, the vast majority of whom had mildly disabling relapsing-remitting MS. Nevertheless, these are the patients who can benefit most from available MS treatments and who are typically included in clinical trials that use MR quantities as additional measures of outcome.1 A trend toward significance was found for the peak height of the MTR histogram and EDSS score and a significant correlation was found between EDSS score and NAA/creatine ratio, explaining in turn 16% and 25% of EDSS variance in our sample. These results are consistent with those from previous studies4,9,11⇓⇓ and indicate that brain axonal viability (as measured by the NAA/creatine ratio) and the amount of “truly normal” NAWM (as measured by the peak height of the MTR histogram)20 are both critical factors in determining MS-related disability. Conversely, however, the magnitude of the correlations found suggests that none of the studied MR quantities taken in isolation account for large proportions of the clinical disability in patients with MS. We therefore built up three composite MR models, each based on three quantities: the extent of macroscopic pathology (T2 lesion volume), the extent of severely damaged lesions (T1 lesion volume), and the overall brain damage in lesions and NAWM (either brain D, NAA/creatine ratio, or MTR). The composite MR scores derived from two of these—model A, using brain D, and model B, using NAA/creatine ratio—were strongly correlated with the EDSS scores. Both models explained about 35% of the variance of disability in our sample.
The next step of the analysis consisted of removal of each of the MR quantities from model A and B in order to obtain models with the least possible redundant information. We found that removing T2 lesion volume from model A did not modify the strength of the correlation. We also found that the largest part of the correlation found for model B was accounted for by brain NAA/creatine ratio. The final step of our analysis was then to assess the degree of the correlation between EDSS scores and composite MR scores derived from another model based on the “best” MR quantities of the previous two models. This composite model included T1 lesion volume, brain D, and brain NAA/creatine ratio and was able to explain about 53% of the variance of disability observed in our sample. This finding suggests that the severity of tissue damage in macroscopic lesions and NAWM are both relevant in determining MS-related disability. Admittedly, the individual items entering composite MR models are likely to vary according to the clinical phenotypes of MS studied and the MR techniques used. As a consequence, further studies based on larger samples of patients with different disease phenotypes are warranted to confirm and extend our results. Nevertheless, this study suggests that multiparametric MR models have the potential to increase our understanding of MS pathophysiology and to provide powerful measures to monitor MS evolution.
Acknowledgments
Supported by grants from the Federazione Italiana Sclerosi Multipla (FISM) and Ministero dell’Università e della Ricerca Scientifica e Tecnologica (project number 9906151218).
- Received October 9, 2000.
- Accepted January 27, 2001.
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