Individual voxel-based subtype prediction can differentiate progressive supranuclear palsy from idiopathic Parkinson syndrome and healthy controls.

Voxel-based morphometry (VBM) shows a differentiated pattern in patients with atypical Parkinson syndrome but so far has had little impact in individual cases. It is desirable to translate VBM findings into clinical practice and individual classification. To this end, we examined whether a support vector machine (SVM) can provide useful accuracies for the differential diagnosis.