Article Figures & Data
Figures
- fig 1.
Typical “normal” MTR histogram shows the parameters H1 through H5
- fig 2.
Typical “normal” array of ordered MTR values, with dotted lines showing the four evenly spaced quadrants used to derive parameters O1 through O8. These parameters simply find the mean and the range of each of the four count-based quadrants
- fig 3.
Mean MTR histograms for the normal volunteer group and the MS subject group.
A and B, Nonnormalized MTR histograms (A) and normalized MTR histograms (B).
- fig 4.
A and B, Normal-to-MS transform. Loss described by the normal-to-MS transform (A) and gain described by the normal-to-MS transform (B). For example, in transforming a normal brain to one representative of the MS data set, approximately 75% of all voxels with an MTR value of 0.5 are removed; 14.4% of them are relocated to lower MTR values in a distribution shown in B, while 85.6% of them are lost. A similar action is performed for voxels with MTR values at other values, although the percentage of loss differs, as shown in A
- fig 5.
Illustration of the three data sets that were used in this study. The last data set (pseudo-MS) was created by putting each of the normal subjects' MTR data through a derived normal-to-MS transform. Since five normal subjects had an average of 4.2 studies each, 21 MTR volumes were transformed in the creation of the five pseudo-MS subjects. The normal-to-MS transform was created through the matching of the mean MTR histograms of the normal data (labeled N 1–5) and the MS data (labeled MS 1–8)
- fig 6.
P values associated with the comparison of the measures shown with respect to normal and MS subjects (filled bars) and with respect to normal subjects and pseudo-MS subjects (open bars). All unlisted measures had P values greater than .05
Tables
P values and their direction of change
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