Voxel-based morphometry in the detection of dysplasia and neoplasia in childhood epilepsy: limitations of grey matter analysis.

The purpose of this exploratory investigation was to evaluate voxel-based morphometry (VBM) in detecting lesions underlying childhood epilepsy, and to establish the optimal image processing and statistical parameters in this context. The patients were 16 children (10 boys) aged 5.9 to 15.2 years (mean 11.3 years) with epilepsy and focal cortical dysplasia (FCD) or neoplasia. The control group comprised 24 normal children (12 boys), age matched to the patients. MRI volumes were spatially normalised to a custom template and segmented into grey matter (GM) and white matter. Using statistical parametric mapping, the GM segment from each patient was then contrasted with the mean GM segment of the control group utilising different VBM post-processing methods. Maps showing increased/decreased areas of GM concentration or volume were generated and compared with visually identified lesions. The results indicated that conservative VBM parameters of linear normalisation with no modulation produced the highest rates of lesion detection, which were identical for FCD and neoplasia at 5/8 lesions. These preliminary data suggest that VBM analysis of GM using conservative parameters can usually detect FCD and neoplasia in the MRI of children with epilepsy, but sensitivity may be inadequate for routine clinical application. Further refinement of the technique may be necessary.