Comparing MRI metrics to quantify white matter microstructural damage in multiple sclerosis

Abstract

Quantifying white matter damage in vivo is becoming increasingly important for investigating the effects of neuroprotective and repair strategies in multiple sclerosis (MS). While various approaches are available, the relationship between MRI-based metrics of white matter microstructure in the disease, that is, to what extent the metrics provide complementary versus redundant information, remains largely unexplored. We obtained four microstructural metrics from 123 MS patients: fractional anisotropy (FA), radial diffusivity (RD), myelin water fraction (MWF), and magnetisation transfer ratio (MTR). Coregistration of maps of these four indices allowed quantification of microstructural damage through voxel-wise damage scores relative to healthy tissue, as assessed in a group of 27 controls. We considered three white matter tissue-states, which were expected to vary in microstructural damage: normal appearing white matter (NAWM), T2-weighted hyperintense lesional tissue without T1-weighted hypointensity (T2L), and T1-weighted hypointense lesional tissue with corresponding T2-weighted hyperintensity (T1L). All MRI indices suggested significant damage in all three tissue-states, the greatest damage being in T1L. The correlations between indices ranged from r = 0.18 to r = 0.87. MWF was most sensitive when differentiating T2L from NAWM, while MTR was most sensitive when differentiating T1L from NAWM and from T2L. Combining the four metrics into one, through a principal component analysis, did not yield a measure more sensitive to damage than any single measure. Our findings suggest that the metrics are (at least partially) correlated with each other, but sensitive to the different aspects of pathology. Leveraging these differences could be beneficial in clinical trials testing the effects of therapeutic interventions.

Keywords: brain MRI; diffusion; lesions; magnetisation transfer ratio; multiple sclerosis; myelin water fraction.

Figure 1

Lesion probability map. The probability map of all white matter lesions detected in all scanned 135 MS patients is shown here. The map shows voxels which were lesioned in at least 5% of the patients (the colour bar ranges from 5% to 50%). The map was used in order to restrict our analyses to white matter regions that are sensitive to the occurrence of lesions. This was done by thresholding the map at 5% and registering the resulting mask to each patient's native space [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 2

Overview of the image processing pipeline. The main analysis steps are outlined, on the left for the tissue‐state segmentation, on the right for the quantification of microstructural damage. Tissue segmentation in patients: Lesion segmentation was performed by two independent operators in order to assess reliability of the lesion segmentation. T1‐weighted images were lesion‐filled and FAST‐segmented in order to obtain a white matter mask. To restrict white matter to lesion‐susceptible regions, a lesion probability map from all patients' individual lesion maps was created and registered to each patient's native space, creating a restricted white matter mask. NAWM was defined as restricted white matter, at least 5 mm away from lesions in order to avoid tissue damage around lesions. White matter lesions were further segmented into T1L and T2L, based on the intensity in the (bias field corrected) T1‐weighted image. The distribution of the intensities on the T1‐weighted image in NAWM voxels is shown in green, while the distribution of the intensities on the T1‐weighted image in lesional voxels is shown in red and in blue. From the distribution of NAWM voxels, a cut‐off was calculated (1.5 IQR below the lower quartile, shown as black line) that was applied to all voxels in the lesion map. Lesional voxels with an intensity below the cut‐off were classified as T1L (red distribution), the rest as T2L (blue distribution). Microstructural damage quantification: For each patient, we derived a parameter map for each FA, RD, MTR, and MWF. We scaled these maps to the distribution (mean and SD) of healthy controls through z‐standardisation, yielding maps of FA(z), RD(z), MTR(z), and MWF(z), respectively. From these, global estimates of damage were obtained from the three segmented tissue‐states. Additionally, voxel‐wise values were considered within each patient's white matter mask in order to (a) look at within‐patient voxel‐wise correlations, (b) combine the four measures through a principal component analysis, and (c) assess sensitivity of each measure to lesional tissue, using a receiver operating characteristic (ROC) analysis. WM: white matter; NAWM: normal appearing white matter; T2L: T2‐hyperintense only lesional tissue; T1L: T2‐hyperintense lesional tissue that appears also T1‐hypointense. FA: fractional anisotropy; RD: radial diffusivity; MTR: magnetisation transfer ratio; MWF: myelin water fraction [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 3

Mean and SD maps for the four parameters in the healthy controls. For each of the metrics, a mean (left) and SD (right) map is shown. The range of displayed values is adjusted to the units of the measures (0–0.5 for FA, MTR, and MWF, and 0–0.001 10⁻³ mm²/s for RD). The low values in the SD maps compared to the mean maps indicate good alignment of white matter structures across the healthy controls. The mean and SD maps were used to compute voxel‐wise tissue damage scores (z‐scores) in patients. Individual maps from 27 (25 for MWF) healthy controls contributed to the mean and SD maps. FA: fractional anisotropy; RD: radial diffusivity; MTR: magnetisation transfer ratio; MWF: myelin water fraction

Figure 4

Estimates of global damage. For each metric, a boxplot across the included 105 patients is shown, comparing global damage estimates for each tissue‐state. Global damage measures were computed as the median z‐score within each tissue‐state for each patient. All differences between tissue‐states are significant for all damage scores as presented in Table 3. NAWM: normal appearing white matter; T2L: T2‐hyperintense only lesional tissue; T1L: T2‐hyperintense lesional tissue that appears also T1‐hypointense; FA(z): z‐score for fractional anisotropy; RD(z): z‐score for radial diffusivity; MTR(z): z‐score for magnetisation transfer ratio; MWF(z): z‐score for myelin water fraction [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 5

Between‐patient correlation coefficients for global damage scores. A correlation matrix is shown for each tissue‐state separately. The absolute correlation coefficient is plotted, as RD correlates negatively with the other metrics. NAWM: normal appearing white matter; T2L: T2‐hyperintense only lesional tissue; T1L: T2‐hyperintense lesional tissue that appears also T1‐hypointense; FA(z): z‐score for fractional anisotropy; RD(z): z‐score for radial diffusivity; MTR(z): z‐score for magnetisation transfer ratio; MWF(z): z‐score for myelin water fraction [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 6

Example scatter plots for between‐patient correlations. a, Relationship between average damage in NAWM as estimated by FA(z) and RD(z). b, Relationship between average damage in T2L as estimated by MTR(z) and MWF(z). c, Relationship between damage in T1L as estimated by MWF(z) and FA(z). NAWM: normal appearing white matter; T2L: T2‐hyperintense only lesional tissue; T1L: T2‐hyperintense lesional tissue that appears also T1‐hypointense; FA(z): z‐score for fractional anisotropy; RD(z): z‐score for radial diffusivity; MTR(z): z‐score for magnetisation transfer ratio; MWF(z): z‐score for myelin water fraction [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 7

ROC analysis. For each patient, a ROC curve was computed for each classification problem: T2L versus NAWM (left plot), T1L versus NAWM (middle plot) and T1L versus T2L (right plot). The patient‐averaged ROC curve (average true positive rate depending on the set false positive rate) is plotted for each metric. To compare the performance of the metrics statistically, we considered each patient's area under the curve and performed pairwise comparisons between the metrics (as described in the text). NAWM: normal appearing white matter; T2L: T2‐hyperintense only lesional tissue; T1L: T2‐hyperintense lesional tissue that appears also T1‐hypointense; FA(z): z‐score for fractional anisotropy; RD(z): z‐score for radial diffusivity; MTR(z): z‐score for magnetisation transfer ratio; MWF(z): z‐score for myelin water fraction, PCA score: score derived from the first principal component of our PCA analysis [Color figure can be viewed at http://wileyonlinelibrary.com]