Classification of childhood white matter disorders using proton MR spectroscopic imaging

Abstract

Background and purpose: Childhood white matter disorders often show similar MR imaging signal-intensity changes, despite different underlying pathophysiologies. The purpose of this study was to determine if proton MR spectroscopic imaging ((1)H-MRSI) may help identify tissue pathophysiology in patients with leukoencephalopathies.

Materials and methods: Seventy patients (mean age, 6; range, 0.66-17 years) were prospectively examined by (1)H-MRSI; a diagnosis of leukoencephalopathy due to known genetic defects leading to lack of formation, breakdown of myelin, or loss of white matter tissue attenuation (rarefaction) was made in 47 patients. The diagnosis remained undefined (UL) in 23 patients. Patients with definite diagnoses were assigned (on the basis of known pathophysiology) to 3 groups corresponding to hypomyelination, white matter rarefaction, and demyelination. Choline (Cho), creatine (Cr), and N-acetylaspartate (NAA) signals from 6 white matter regions and their intra- and intervoxel (relative to gray matter) ratios were measured. Analysis of variance was performed by diagnosis and by pathophysiology group. Stepwise linear discriminant analysis was performed to construct a model to predict pathophysiology on the basis of (1)H-MRSI, and was applied to the UL group.

Results: Analysis of variance by diagnosis showed 3 main metabolic patterns. Analysis of variance by pathophysiology showed significant differences for Cho/NAA (P < .001), Cho/Cr (P < .004), and NAA/Cr (P < .002). Accuracy of the linear discriminant analysis model was 75%, with Cho/Cr and NAA/Cr being the best parameters for classification. On the basis of the linear discriminant analysis model, 61% of the subjects in the UL group were classified as hypomyelinating.

Conclusion: (1)H-MRSI provides information on tissue pathophysiology and may, therefore, be a valuable tool in the evaluation of patients with leukoencephalopathies.

Fig 1.

T2-weighted MR, selected spectra, and metabolic images of Cho, Cr, NAA, and lactate (Lac) in a typical case of hypomyelination (Pelizaeus-Merzbacher disease). Spectral patterns from both white and gray matter show near-normal profiles, with a large NAA signal intensity and near-equal Cho and Cr. Bright signal at the corners of the metabolic images arises from residual lipid signals from the scalp. PPM indicates parts per million.

Fig 2.

T2-weighted MR, selected spectra, and metabolic images of Cho, Cr, NAA, and lactate (Lac) in a case of rarefaction of white matter (LVWM). Metabolic images clearly show decreased Cr and NAA in T2-hyperintense white matter regions, whereas Cho is largely unchanged. In white matter voxels, the NAA/Cho ratio is approximately 1:1. This patient was diagnosed with LVWM at a very early stage and is 1 of the 2 patients with LVWM misclassified in group 1. PPM indicates parts per million.

Fig 3.

T2-weighted MR, selected spectra, and metabolic images of Cho, Cr, NAA, and lactate (Lac) in a typical demyelination case (metachromatic leukodystrophy). T2-hyperintense white matter regions are characterized by increased Cho and decreased NAA. The gray matter spectrum (voxel 4) also shows a somewhat decreased NAA/Cho ratio. PPM indicates parts per million.

Fig 4.

T2-weighted MR, selected spectra, and metabolic images of Cho, Cr, NAA, and lactate (Lac) in a typical patient with Canavan disease. NAA is higher than normal in both white and gray matter regions. Note lower (ie, more normal) NAA levels, as seen in voxel 2 and in the NAA metabolic image, in the deeper white matter where there is less signal-intensity abnormality on the T2-weighted MR image. PPM indicates parts per million.