SMART-PET: multimodality white matter imaging and display without loss of quantitative information.

PURPOSE

To improve analysis of cerebral white matter (WM) in fluoro-deoxy-glucose positron emission tomography (PET) images.

MATERIALS AND METHODS

A multimodality analysis technique (segmented MRI and registered Talairach-transformed PET [SMART-PET]) was used for quantitative assessment of WM metabolism. Data processing included Talairach transformation of three-dimensional magnetic resonance imaging (MRI) and subsequent automated segmentation and coregistration to normalized PET images. Color model transformations were used for combined display: the hue saturation value color model was regarded as a three-dimensional data matrix, integrating quantitative voxel data of both modalities. The technique was applied in normal subjects and in patients suffering from different WM diseases. Regional analysis was performed to classify metabolic impairment on a five-point scale.

RESULTS

Using SMART-PET, a considerable gain in image contrast for WM was achieved in all cases. In the normal subjects, WM metabolism was shown to be homogeneously unimpaired. Sum scores of regional analysis revealed metabolic WM changes in all patients. Extent of WM hypometabolism exceeded the extent of the lesions as delineated by MRI signal changes.

CONCLUSION

The potential of the method for further elucidation of the role of WM diseases in brain dysfunction in patients is discussed.